diff --git a/.gitignore b/.gitignore
index 5c417f9..755244c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,6 +7,8 @@
# Generated files
.docusaurus
.cache-loader
+docusaurus.config.js
+sidebars.js
# Misc
.DS_Store
@@ -15,6 +17,10 @@
.env.test.local
.env.production.local
+# Lock files - use pnpm-lock.yaml only
+package-lock.json
+yarn.lock
+
npm-debug.log*
yarn-debug.log*
yarn-error.log*
diff --git a/.husky/commit-msg b/.husky/commit-msg
new file mode 100644
index 0000000..b5ff712
--- /dev/null
+++ b/.husky/commit-msg
@@ -0,0 +1,4 @@
+#!/bin/sh
+. "$(dirname "$0")/_/husky.sh"
+
+bunx commitlint --edit $1
diff --git a/.husky/pre-commit b/.husky/pre-commit
new file mode 100644
index 0000000..d28fd9d
--- /dev/null
+++ b/.husky/pre-commit
@@ -0,0 +1,4 @@
+#!/bin/sh
+. "$(dirname "$0")/_/husky.sh"
+
+bun run lint-staged
diff --git a/.prettierignore b/.prettierignore
new file mode 100644
index 0000000..e811cfe
--- /dev/null
+++ b/.prettierignore
@@ -0,0 +1,27 @@
+# Dependencies
+node_modules/
+
+# Build outputs
+.next/
+out/
+dist/
+build/
+
+# Environment files
+.env*
+
+# Logs
+*.log
+
+# Package manager files
+package-lock.json
+yarn.lock
+pnpm-lock.yaml
+
+# IDE files
+.vscode/
+.idea/
+
+# OS files
+.DS_Store
+Thumbs.db
diff --git a/.prettierrc b/.prettierrc
new file mode 100644
index 0000000..7e00f80
--- /dev/null
+++ b/.prettierrc
@@ -0,0 +1,13 @@
+{
+ "semi": true,
+ "trailingComma": "es5",
+ "singleQuote": true,
+ "tabWidth": 2,
+ "useTabs": false,
+ "printWidth": 80,
+ "bracketSpacing": true,
+ "arrowParens": "avoid",
+ "endOfLine": "lf",
+ "jsxSingleQuote": false,
+ "bracketSameLine": false
+}
diff --git a/README.md b/README.md
index e46fcbd..27a53f9 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,6 @@ Internal documentation site for CROW project.
## Setup
```bash
-pnpm install
-pnpm start
+bun install
+bun start
```
diff --git a/bun.lock b/bun.lock
new file mode 100644
index 0000000..c2f1403
--- /dev/null
+++ b/bun.lock
@@ -0,0 +1,3143 @@
+{
+ "lockfileVersion": 1,
+ "configVersion": 1,
+ "workspaces": {
+ "": {
+ "name": "crow-b3-internal-docs",
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+ "@docusaurus/core": "3.9.2",
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+ "prism-react-renderer": "^2.3.0",
+ "react": "^19.0.0",
+ "react-dom": "^19.0.0",
+ },
+ "devDependencies": {
+ "@antfu/eslint-config": "^6.7.1",
+ "@commitlint/config-conventional": "^20.2.0",
+ "@docusaurus/module-type-aliases": "3.9.2",
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+ "husky": "^9.1.7",
+ "lint-staged": "^16.2.7",
+ "prettier": "^3.7.4",
+ "typescript": "~5.6.2",
+ },
+ },
+ },
+ "trustedDependencies": [
+ "husky",
+ "@docusaurus/core",
+ ],
+ "packages": {
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+ "update-notifier/boxen/wrap-ansi/ansi-styles": ["ansi-styles@6.2.3", "", {}, "sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg=="],
+
+ "webpackbar/wrap-ansi/string-width/emoji-regex": ["emoji-regex@8.0.0", "", {}, "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A=="],
+
+ "webpackbar/wrap-ansi/strip-ansi/ansi-regex": ["ansi-regex@5.0.1", "", {}, "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ=="],
+
+ "pkg-dir/find-up/locate-path/p-locate/p-limit": ["p-limit@4.0.0", "", { "dependencies": { "yocto-queue": "1.2.1" } }, "sha512-5b0R4txpzjPWVw/cXXUResoD4hb6U/x9BH08L7nw+GN1sezDzPdxeRvpc9c433fZhBan/wusjbCsqwqm4EIBIQ=="],
+
+ "pkg-dir/find-up/locate-path/p-locate/p-limit/yocto-queue": ["yocto-queue@1.2.1", "", {}, "sha512-AyeEbWOu/TAXdxlV9wmGcR0+yh2j3vYPGOECcIj2S7MkrLyC7ne+oye2BKTItt0ii2PHk4cDy+95+LshzbXnGg=="],
+ }
+}
diff --git a/commitlint.config.cjs b/commitlint.config.cjs
new file mode 100644
index 0000000..5a4dd59
--- /dev/null
+++ b/commitlint.config.cjs
@@ -0,0 +1,4 @@
+module.exports = {
+ extends: ["@commitlint/config-conventional"],
+ rules: {},
+};
diff --git a/docs/architecture/_category_.json b/docs/architecture/_category_.json
new file mode 100644
index 0000000..7ef07dd
--- /dev/null
+++ b/docs/architecture/_category_.json
@@ -0,0 +1,5 @@
+{
+ "label": "Architecture",
+ "position": 2,
+ "collapsed": false
+}
diff --git a/docs/architecture/data-lake-architecture.md b/docs/architecture/data-lake-architecture.md
new file mode 100644
index 0000000..9795b1d
--- /dev/null
+++ b/docs/architecture/data-lake-architecture.md
@@ -0,0 +1,495 @@
+---
+sidebar_position: 4
+---
+
+# Data Storage Architecture
+
+## Overview
+
+The CROW Data Storage Architecture is built entirely on Cloudflare's edge infrastructure, providing efficient storage, processing, and retrieval of interaction data from various sources including websites, CCTV, and social media. This architecture leverages D1 (relational database), R2 (object storage), and Vectorize (vector database) for a unified, globally distributed storage solution.
+
+## Architecture Components
+
+### 1. D1 Database
+
+Cloudflare D1 serves as the primary relational database for structured data:
+
+- **Structured Data**: Users, organizations, products, API keys
+- **Interaction Metadata**: Session info, timestamps, sources
+- **Processing State**: Job status, workflow state
+- **Configuration**: Settings, preferences, rules
+
+**Key Features:**
+- SQLite-based with familiar SQL syntax
+- Automatic global replication
+- Point-in-time recovery
+- Sub-millisecond read latency at edge
+
+### 2. R2 Object Storage
+
+Cloudflare R2 provides S3-compatible object storage:
+
+- **Raw Interactions**: Original event payloads
+- **CCTV Frames**: Extracted video frames
+- **Export Files**: Generated reports (PDF, CSV)
+- **Assets**: Images, documents, attachments
+
+**Key Features:**
+- Zero egress fees
+- S3 API compatibility
+- Automatic global distribution
+- Lifecycle policies for data retention
+
+### 3. Vectorize
+
+Cloudflare Vectorize provides AI-native vector storage and search:
+
+- **Interaction Embeddings**: Vectorized interaction text from all sources
+- **Product Embeddings**: Product description vectors
+- **Social Embeddings**: Social media content vectors
+- **Organization Context**: Organization-specific context embeddings
+- **Pattern Embeddings**: Discovered pattern vectors
+
+**Key Features:**
+- High-dimensional vector storage (1536 dimensions for Gemini embeddings)
+- Fast similarity search
+- Metadata filtering
+- Automatic index optimization
+- Used by Chat Service for semantic search
+
+### 4. Durable Objects
+
+Cloudflare Durable Objects for stateful session management:
+
+- **Web Session State**: Active user session tracking
+- **Inactivity Alarms**: Automatic 1-hour inactivity triggers
+- **Builder State**: Signup flow state management
+
+**Key Features:**
+- Strong consistency
+- Low-latency state access
+- Automatic alarm triggers
+- Per-session isolation
+
+## Data Flow
+
+### Ingestion Flow
+
+```mermaid
+flowchart TD
+ A[Raw Data
Web/Social/CCTV] --> B[Component Worker
or Durable Object]
+ B --> C[Cloudflare Queue]
+ C --> D[Interaction Service]
+ D --> E{Process with Gemini AI}
+ E --> F[Generate Text Description]
+ E --> G[Extract Metadata]
+ F --> H[Store Raw in R2
Optional]
+ F --> I[Generate Embeddings
Gemini via Vercel AI SDK]
+ G --> J[Store in D1
Metadata]
+ I --> K[Store in Vectorize
Semantic Search]
+ D --> L[Analytics Service
Billing Tracking]
+```
+
+### Storage Architecture
+
+```mermaid
+graph TB
+ subgraph "Cloudflare R2"
+ A[Raw Interaction Files]
+ B[Chat Artifacts & Assets]
+ C[Export Files]
+ end
+
+ subgraph "Cloudflare D1"
+ D[Interaction/Pattern Metadata]
+ E[User & Org Data]
+ F[Product Catalog]
+ G[API Keys & Sessions]
+ H[Chat History]
+ I[Notifications]
+ end
+
+ subgraph "Cloudflare Vectorize"
+ J[Interaction Embeddings]
+ K[Product Embeddings]
+ L[Social Embeddings]
+ M[Organization Context]
+ N[Pattern Embeddings]
+ end
+
+ subgraph "Cloudflare Durable Objects"
+ O[Web Session State]
+ P[Builder Flow State]
+ end
+
+ A -.stored in.-> R2
+ B -.stored in.-> R2
+ C -.stored in.-> R2
+ D -.indexed.-> D1
+ E -.indexed.-> D1
+ F -.indexed.-> D1
+ J -.indexed.-> Vectorize
+ K -.indexed.-> Vectorize
+ L -.indexed.-> Vectorize
+```
+
+### Retrieval Flow
+
+```mermaid
+sequenceDiagram
+ participant Client as Dashboard/API Client
+ participant Gateway as API Gateway
+ participant Service as Data Service
+ participant D1
+ participant Vectorize
+ participant R2
+
+ Client->>Gateway: Search/Query Request
+ Gateway->>Gateway: Validate Session/API Key
+ Gateway->>Gateway: Issue JWT
+ Gateway->>Service: Forward with JWT
+ Service->>D1: Pre-filter by criteria
+ D1-->>Service: Filtered metadata
+ Service->>Vectorize: Semantic search
+ Vectorize-->>Service: Matching IDs with scores
+ Service->>D1: Fetch full metadata
+ D1-->>Service: Complete data
+ Service->>R2: Retrieve artifacts (if needed)
+ R2-->>Service: Files/content
+ Service-->>Gateway: Results
+ Gateway-->>Client: Search Results
+```
+
+## Detailed Process Flow
+
+### 1. New Interaction Processing
+
+When a new interaction is received from any component (Web, Social, CCTV):
+
+1. **Reception**: Component Worker or Durable Object receives raw data
+2. **Queue Dispatch**: Session data sent to Interaction Queue
+3. **Interaction Service**: Consumes queue message
+4. **Context Retrieval**: Fetches Organization and Product context
+5. **AI Processing**: Gemini AI analyzes data via Vercel AI SDK
+6. **Storage**:
+ - **D1**: Metadata record with unique ID, source, timestamps
+ - **R2**: Raw payload (optional, for archival)
+ - **Vectorize**: Text embeddings for semantic search
+7. **Analytics**: Notifies Analytics Service for billing tracking
+
+### 2. Pattern Discovery
+
+Pattern Service processes interactions periodically:
+
+1. **Cron Trigger**: Daily execution
+2. **Retrieve Interactions**: Last 24 hours from D1/Vectorize
+3. **Context Enrichment**: Add Organization and Product context
+4. **AI Analysis**: Gemini AI identifies patterns via Vercel AI SDK
+5. **Storage**:
+ - **D1**: Pattern metadata with time period (day, week, month, year)
+ - **Vectorize**: Pattern embeddings
+6. **Self-triggering**: Queue messages for multi-period aggregation
+
+### 3. Data Retrieval Process
+
+When retrieving data (Dashboard, Chat, API):
+
+1. **Authentication**: Gateway validates session/API key, issues JWT
+2. **Pre-filtering**: Service queries D1 by criteria (date, product, source, org)
+3. **Semantic Search**: Vectorize performs vector similarity search
+4. **Results Assembly**: Matching IDs fetch complete metadata from D1
+5. **Optional Raw Data**: Retrieve original content from R2 if needed
+6. **Permission Check**: Validate user has access to requested data
+
+## Database Schema (D1)
+
+### Core Tables
+
+```sql
+-- Organizations
+CREATE TABLE organizations (
+ id TEXT PRIMARY KEY,
+ name TEXT NOT NULL,
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
+ settings JSON
+);
+
+-- Users (1:1 with Organizations)
+CREATE TABLE users (
+ id TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL REFERENCES organizations(id),
+ email TEXT UNIQUE NOT NULL,
+ username TEXT,
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+
+-- User Permissions
+CREATE TABLE user_permissions (
+ user_id TEXT PRIMARY KEY REFERENCES users(id),
+ -- Chat constraints
+ chat_enabled BOOLEAN DEFAULT true,
+ chat_min_duration TEXT DEFAULT '1yr',
+ chat_components JSON DEFAULT '["web"]',
+ -- Feature toggles
+ interactions_enabled BOOLEAN DEFAULT true,
+ patterns_enabled BOOLEAN DEFAULT true,
+ teams_enabled BOOLEAN DEFAULT false,
+ api_keys_enabled BOOLEAN DEFAULT false,
+ billing_enabled BOOLEAN DEFAULT false,
+ settings_enabled BOOLEAN DEFAULT false,
+ notifications_enabled BOOLEAN DEFAULT true,
+ integrations_enabled BOOLEAN DEFAULT false,
+ products_enabled BOOLEAN DEFAULT false,
+ updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+
+-- API Keys
+CREATE TABLE api_keys (
+ id TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL REFERENCES organizations(id),
+ key_hash TEXT NOT NULL,
+ name TEXT,
+ expires_at DATETIME,
+ -- Permissions
+ interactions_enabled BOOLEAN DEFAULT true,
+ patterns_enabled BOOLEAN DEFAULT true,
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
+ last_used DATETIME
+);
+
+-- Products
+CREATE TABLE products (
+ id TEXT PRIMARY KEY,
+ org_id TEXT REFERENCES organizations(id),
+ name TEXT NOT NULL,
+ description TEXT,
+ metadata JSON
+);
+
+-- Interactions
+CREATE TABLE interactions (
+ id TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL REFERENCES organizations(id),
+ session_id TEXT NOT NULL,
+ source TEXT NOT NULL, -- 'web', 'social', 'cctv'
+ description TEXT, -- AI-generated textual description
+ products JSON, -- Array of product IDs involved
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
+ metadata JSON,
+ vector_id TEXT -- Reference to Vectorize embedding
+);
+
+-- Patterns
+CREATE TABLE patterns (
+ id TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL REFERENCES organizations(id),
+ time_period TEXT NOT NULL, -- 'day', 'week', 'month', 'year', 'all_time'
+ description TEXT, -- AI-generated pattern description
+ products JSON, -- Array of product IDs involved
+ confidence REAL, -- Pattern confidence score
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
+ metadata JSON,
+ vector_id TEXT
+);
+
+-- Chat History
+CREATE TABLE chat_sessions (
+ id TEXT PRIMARY KEY,
+ user_id TEXT NOT NULL REFERENCES users(id),
+ org_id TEXT NOT NULL REFERENCES organizations(id),
+ title TEXT,
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
+ updated_at DATETIME
+);
+
+CREATE TABLE chat_messages (
+ id TEXT PRIMARY KEY,
+ session_id TEXT NOT NULL REFERENCES chat_sessions(id),
+ role TEXT NOT NULL, -- 'user' or 'assistant'
+ content TEXT NOT NULL,
+ artifacts JSON, -- Generated files, charts, etc.
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+
+-- Notifications
+CREATE TABLE notifications (
+ id TEXT PRIMARY KEY,
+ user_id TEXT NOT NULL REFERENCES users(id),
+ type TEXT NOT NULL,
+ title TEXT NOT NULL,
+ content TEXT,
+ read BOOLEAN DEFAULT false,
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+
+-- Social Media Link Tracking
+CREATE TABLE seen_links (
+ url TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL,
+ first_seen DATETIME DEFAULT CURRENT_TIMESTAMP,
+ last_checked DATETIME,
+ content_hash TEXT,
+ source TEXT -- 'search' or 'direct'
+);
+```
+
+## R2 Bucket Structure
+
+```
+crow-storage/
+├── raw/
+│ ├── interactions/
+│ │ └── {org_id}/{component}/{date}/{interaction_id}.json
+│ └── sessions/
+│ └── {org_id}/{component}/{session_id}.json
+├── chat/
+│ ├── artifacts/
+│ │ └── {org_id}/{chat_id}/{artifact_id}
+│ └── assets/
+│ └── {org_id}/{chat_id}/{asset_id}
+├── exports/
+│ └── {org_id}/{export_id}/{filename}
+└── products/
+ └── {org_id}/{product_id}/{image}
+```
+
+**Directory Purposes:**
+- `raw/`: Optional raw interaction and session data archival
+- `chat/`: Chat-generated artifacts (reports, charts) and assets (images)
+- `exports/`: User-requested data exports (CSV, PDF, JSON)
+- `products/`: Product images and media
+
+## Vectorize Indexes
+
+### interaction-embeddings
+
+- **Dimensions**: 1536 (Gemini embeddings)
+- **Metric**: Cosine similarity
+- **Metadata**: org_id, source (web/social/cctv), session_id, created_at
+- **Purpose**: Semantic search across all interactions
+
+### pattern-embeddings
+
+- **Dimensions**: 1536 (Gemini embeddings)
+- **Metric**: Cosine similarity
+- **Metadata**: org_id, time_period, confidence, created_at
+- **Purpose**: Pattern discovery and trend analysis
+
+### product-embeddings
+
+- **Dimensions**: 1536 (Gemini embeddings)
+- **Metric**: Cosine similarity
+- **Metadata**: org_id, category, price_range
+- **Purpose**: Product similarity and recommendations
+
+### organization-context-embeddings
+
+- **Dimensions**: 1536 (Gemini embeddings)
+- **Metric**: Cosine similarity
+- **Metadata**: org_id, context_type, updated_at
+- **Purpose**: Organization-specific context for AI processing
+
+**All embeddings generated via Gemini AI through Vercel AI SDK**
+
+## Technology Stack
+
+| Component | Cloudflare Service | Purpose |
+|-----------|-------------------|---------|
+| Relational DB | D1 | Structured data, metadata |
+| Object Storage | R2 | Raw data, files, exports, chat artifacts |
+| Vector DB | Vectorize | Semantic search, AI embeddings |
+| Session State | Durable Objects | Web session management, builder state |
+| Caching | Workers KV | Session cache, JWT mapping (1-5 min TTL) |
+| Queuing | Queues | Async processing, service communication |
+
+**AI Technology:**
+- **Models**: Google Gemini (all AI processing)
+- **Framework**: Vercel AI SDK (agent orchestration)
+- **Gateway**: Cloudflare AI Gateway (LLM request routing)
+
+## Advantages
+
+### Cloudflare Platform Benefits
+
+- **Global Distribution**: Data served from 300+ edge locations
+- **Zero Egress**: No fees for data transfer out of R2
+- **Integrated**: Seamless connectivity between D1, R2, Vectorize
+- **Simplified Operations**: No server management required
+- **Cost Effective**: Pay-per-use pricing model
+
+### Architecture Benefits
+
+- **Separation of Concerns**: Relational, object, and vector data stored optimally
+- **Flexibility**: Each layer optimized for its specific use case
+- **Scalability**: Cloudflare manages scaling automatically
+- **Performance**: Edge distribution ensures low latency globally
+
+## Data Retention & Lifecycle
+
+### Retention Policies
+
+- **Interactions Metadata**: Retained indefinitely in D1
+- **Pattern Metadata**: Retained indefinitely (all time periods)
+- **Raw Interaction Data**: Optional archival in R2 (30 days hot, then archive)
+- **Chat History**: Retained indefinitely
+- **Chat Artifacts**: 30 days in R2
+- **Exports**: 7 days in R2, auto-deleted after
+- **Session Cache**: 1-5 minutes TTL in Workers KV
+
+**Privacy Compliance:**
+- **GDPR**: User can request data deletion from settings
+- **Organization Context**: Clearable from dashboard
+- **CCTV Data**: Not stored long-term (processed in real-time)
+
+### R2 Lifecycle Rules
+
+```javascript
+{
+ "rules": [
+ {
+ "id": "archive-raw-interactions",
+ "filter": { "prefix": "raw/interactions/" },
+ "transitions": [
+ { "days": 30, "storageClass": "ARCHIVE" }
+ ]
+ },
+ {
+ "id": "delete-chat-artifacts",
+ "filter": { "prefix": "chat/" },
+ "expiration": { "days": 30 }
+ },
+ {
+ "id": "delete-exports",
+ "filter": { "prefix": "exports/" },
+ "expiration": { "days": 7 }
+ }
+ ]
+}
+```
+
+## Future Considerations
+
+### Scalability Planning
+
+- Monitor D1 database size and query patterns
+- Implement data partitioning if needed
+- Plan for multi-region data residency requirements
+
+### Performance Optimization
+
+- Implement caching layer with Workers KV
+- Optimize Vectorize index configuration
+- Consider hybrid search (vector + keyword)
+
+### Compliance
+
+- GDPR data deletion workflows
+- Data residency controls
+- Audit logging for access
+
+## Glossary
+
+- **D1**: Cloudflare's serverless SQLite database
+- **R2**: Cloudflare's S3-compatible object storage
+- **Vectorize**: Cloudflare's vector database for AI embeddings
+- **Embeddings**: Numerical vector representations of text
diff --git a/docs/architecture/frontend-architecture.md b/docs/architecture/frontend-architecture.md
new file mode 100644
index 0000000..1e24fba
--- /dev/null
+++ b/docs/architecture/frontend-architecture.md
@@ -0,0 +1,286 @@
+---
+sidebar_position: 2
+---
+
+# Frontend Architecture
+
+## Overview
+
+The CROW platform frontend is built on Cloudflare's edge infrastructure with a split architecture approach that separates public-facing content from authenticated user workspaces. Both applications are deployed as Cloudflare Workers, ensuring global low-latency access and simplified operations.
+
+## Split Frontend Design
+
+The CROW platform utilizes a **split frontend architecture** with three separate applications:
+
+1. **Landing Client** - Public-facing marketing and product information
+2. **Auth Client** - Dedicated authentication and onboarding flows
+3. **Dashboard Client** - Authenticated user workspace with analytics and chat
+
+### Why Split Frontend?
+
+The frontend is intentionally split into three separate applications to:
+
+- **Building Block Approach**: Clients are modular and can be rearranged or deployed independently
+- **Optimize Bundle Size**: Each client only ships what it needs
+- **Independent Deployment**: Each application deploys separately via Cloudflare Workers
+- **Future Flexibility**: Easy to add new clients (e.g., mobile/desktop home page)
+- **Better SEO**: Different pages optimized separately
+- **Tech Stack Freedom**: Each client can use different technologies if needed
+- **Clear Separation**: Distinct boundaries between public, auth, and private areas
+
+### Application Purposes
+
+#### Landing Client
+- **Purpose**: Marketing, product information, and public content
+- **Features**:
+ - Product showcase
+ - Pricing information
+ - Company information
+ - Documentation links
+- **Optimization**: Minimal JavaScript, fast load times, SEO-optimized
+- **No Authentication**: Purely public-facing content
+
+#### Auth Client
+- **Purpose**: User authentication and organization onboarding
+- **Features**:
+ - User signup with organization creation
+ - User login
+ - Invited user flows
+ - Session initialization
+ - Organization setup and product onboarding
+ - Payment flow integration
+ - Component configuration (Web, Social, CCTV)
+- **Session Management**: Initializes sessions that are passed to dashboard client
+- **Integration**: Works with Better Auth for session-based authentication
+
+#### Dashboard Client
+- **Purpose**: Authenticated user workspace and platform management
+- **Features**:
+ - Organization overview
+ - Product catalog management
+ - Chat interface for data queries (multi-agentic)
+ - Insights and patterns visualization
+ - Team management
+ - Notifications
+ - Billing and analytics
+ - Settings (API Keys, Integrations, Profile, Product Management, Webhooks)
+- **Optimization**: Rich interactivity, real-time updates, comprehensive tooling
+
+## Deployment on Cloudflare Workers
+
+Both frontend applications are deployed on **Cloudflare Workers**, leveraging their global edge network.
+
+### Technology Stack
+
+| Technology | Purpose | Version |
+|------------|---------|---------|
+| **Next.js** | React framework with SSR/SSG | 15+ |
+| **TypeScript** | Static type checking | 5.x |
+| **TailwindCSS** | Utility-first CSS framework | 4.x |
+| **shadcn/ui** | Component library (Radix UI based) | Latest |
+| **Bun** | Package manager and local dev tooling | 1.x |
+| **Cloudflare Workers/Pages** | Edge deployment | N/A |
+| **Cloudflare Images** | Image optimization | N/A |
+
+**Note on Bun**: While Bun includes its own JS runtime, CROW uses Bun specifically for package management. Cloudflare Workers run on the V8 JS engine, not JavaScriptCore.
+
+### Cloudflare Workers Advantages
+
+**Global Edge Network**
+- Content served from 300+ locations worldwide
+- Requests routed to the closest data center to users
+- Automatic geographic load balancing
+
+**Ultra-Low Latency**
+- Response times under 50ms globally
+- No cold starts unlike traditional serverless
+- V8 isolates start in less than 5ms
+
+**DDoS Protection**
+- Built-in protection against attacks
+- Automatic mitigation of malicious traffic
+- Enterprise-grade security at the edge
+
+**Auto-scaling**
+- Handles traffic spikes automatically without configuration
+- No manual scaling required
+- Infinite scalability for static and dynamic content
+
+**Cost Efficiency**
+- Pay-per-request pricing model
+- No charges for idle time
+- Predictable costs based on actual usage
+
+**Global Availability**
+- 100% uptime SLA
+- Automatic failover
+- No single point of failure
+
+**Developer Experience**
+- Simple deployment workflow
+- Built-in versioning and rollbacks
+- Instant preview deployments
+
+## Architecture Diagram
+
+```mermaid
+graph TB
+ subgraph "Users"
+ PublicUser[Public Visitor]
+ NewUser[New User]
+ AuthUser[Authenticated User]
+ end
+
+ subgraph "Cloudflare Edge Network"
+ subgraph "Landing Client"
+ LandingWorker[Landing Worker
React/Next.js]
+ end
+
+ subgraph "Auth Client"
+ AuthWorker[Auth Worker
React/Next.js]
+ end
+
+ subgraph "Dashboard Client"
+ DashboardWorker[Dashboard Worker
React/Next.js]
+ end
+ end
+
+ subgraph "Backend Services"
+ API[Core API Layer]
+ Auth[Auth Service]
+ end
+
+ PublicUser --> LandingWorker
+ NewUser --> AuthWorker
+ AuthWorker --> Auth
+ Auth --> DashboardWorker
+
+ AuthUser --> DashboardWorker
+ DashboardWorker --> API
+ DashboardWorker --> Auth
+```
+
+## Request Flow
+
+### New User Signup Flow
+
+```mermaid
+sequenceDiagram
+ participant User
+ participant CF as Cloudflare Edge
+ participant Landing as Landing Client
+ participant AuthClient as Auth Client
+ participant AuthSvc as Auth Service
+ participant Dashboard as Dashboard Client
+
+ User->>CF: Visit landing page
+ CF->>Landing: Route to nearest edge
+ Landing-->>User: Landing page
+
+ User->>Landing: Click Sign Up
+ Landing-->>User: Redirect to Auth Client
+
+ User->>AuthClient: Sign up form
+ AuthClient->>AuthSvc: Create account
+ AuthSvc-->>AuthClient: Account created
+
+ AuthClient->>AuthClient: Organization creation
+ AuthClient->>AuthClient: Product sync setup
+ AuthClient->>AuthClient: Payment flow
+ AuthClient->>AuthClient: Component configuration
+
+ AuthClient->>AuthSvc: Initialize session
+ AuthSvc-->>AuthClient: Session token
+ AuthClient-->>User: Redirect to Dashboard
+
+ User->>Dashboard: Access dashboard
+ Dashboard->>AuthSvc: Validate session
+ AuthSvc-->>Dashboard: Authorized
+ Dashboard-->>User: Dashboard loaded
+```
+
+### Dashboard Request Flow
+
+```mermaid
+sequenceDiagram
+ participant User
+ participant CF as Cloudflare Edge
+ participant Dashboard as Dashboard Client
+ participant API as Core API
+ participant Auth as Auth Service
+
+ User->>CF: Request dashboard
+ CF->>Dashboard: Route to nearest edge
+ Dashboard->>Auth: Validate session
+ Auth-->>Dashboard: Authorized
+ Dashboard->>API: Fetch user data
+ API-->>Dashboard: User data
+ Dashboard-->>User: Rendered dashboard
+```
+
+## Performance Characteristics
+
+### Landing Client
+- **First Contentful Paint**: < 0.5s
+- **Time to Interactive**: < 1s
+- **Lighthouse Score**: 95+ (Performance, SEO, Accessibility)
+- **Bundle Size**: < 100KB (gzipped)
+
+### Auth Client
+- **First Contentful Paint**: < 0.8s
+- **Time to Interactive**: < 1.5s
+- **Lighthouse Score**: 90+ (Performance, Accessibility)
+- **Bundle Size**: Optimized for signup flows
+
+### Dashboard Client
+- **First Contentful Paint**: < 1s
+- **Time to Interactive**: < 2s
+- **Lighthouse Score**: 90+ (Performance, Accessibility)
+- **Bundle Size**: Optimized with code splitting
+
+## Security Considerations
+
+### Landing Client Security
+- **Public Access**: No authentication required
+- **HTTPS Only**: All traffic encrypted with TLS 1.3
+- **CSP Headers**: Content Security Policy to prevent XSS
+- **Rate Limiting**: Protection against abuse
+
+### Auth Client Security
+- **Session-Based Auth**: Better Auth with Drizzle ORM
+- **HTTPS Only**: All traffic encrypted with TLS 1.3
+- **CSRF Protection**: Anti-CSRF tokens for state-changing operations
+- **Secure Session Storage**: Session tokens properly managed
+- **Rate Limiting**: Protection against brute force attacks
+
+### Dashboard Client Security
+- **Authentication Required**: Session-based authentication with Better Auth
+- **Authorization**: Permission-based access control (see User Permission Levels)
+- **HTTPS Only**: All traffic encrypted
+- **CSRF Protection**: Anti-CSRF tokens for state-changing operations
+- **Session Management**: Secure session handling with automatic expiry
+- **Organization Scoping**: 1:1 user-organization data isolation
+
+## Deployment Strategy
+
+### Continuous Deployment
+
+Both applications use continuous deployment:
+
+1. **Code Push**: Developer pushes code to repository
+2. **CI/CD Pipeline**: Automated build and test
+3. **Preview Deployment**: Temporary preview URL for testing
+4. **Production Deployment**: Deploy to Cloudflare Workers edge network
+5. **Instant Propagation**: Changes propagate globally in seconds
+
+### Rollback Strategy
+
+- **Instant Rollback**: Previous versions kept for instant rollback
+- **Gradual Rollout**: Optional percentage-based traffic splitting
+- **Automatic Rollback**: Configured based on error rate thresholds
+
+## Related Documentation
+
+- [User Signup Flow](../features/user-signup-flow.md) - User registration process
+- [System Architecture](./system-architecture.md) - Overall platform architecture
+- [Integration API](./integration-api.md) - API integration details
diff --git a/docs/architecture/integration-api.md b/docs/architecture/integration-api.md
new file mode 100644
index 0000000..6c50d4d
--- /dev/null
+++ b/docs/architecture/integration-api.md
@@ -0,0 +1,220 @@
+---
+sidebar_position: 5
+---
+
+# Integration API
+
+## Overview
+
+The CROW platform exposes a comprehensive **Integration API Layer** built on Cloudflare Workers, providing global low-latency access for both internal and external consumers. The API layer supports REST, GraphQL, Agent2Agent (A2A), and MCP protocols.
+
+## Architecture
+
+```mermaid
+graph TB
+ subgraph "API Consumers"
+ Dashboard[Dashboard App]
+ External[External Clients]
+ LLMs[LLM Agents]
+ end
+
+ subgraph "Cloudflare Workers"
+ REST[REST API Worker]
+ GQL[GraphQL Worker]
+ A2A[A2A Worker]
+ MCP[MCP Server Worker]
+ end
+
+ subgraph "Storage"
+ D1[D1 Database]
+ R2[R2 Storage]
+ Vec[Vectorize]
+ end
+
+ Dashboard --> REST
+ Dashboard --> GQL
+ External --> REST
+ External --> GQL
+ LLMs --> A2A
+ LLMs --> MCP
+
+ REST --> D1
+ REST --> R2
+ GQL --> D1
+ GQL --> Vec
+ A2A --> D1
+ A2A --> Vec
+ MCP --> D1
+ MCP --> Vec
+```
+
+## API Types
+
+CROW provides multiple API access methods optimized for different use cases.
+
+### 1. REST API
+
+**Audience**: External clients, mobile apps, web applications, dashboard
+
+**Features**:
+- Edge Deployment: Runs on Cloudflare Workers globally
+- Authentication: API key and session-based auth
+- Rate Limiting: Configurable per-key limits
+- Versioning: URL-based versioning (v1, v2)
+- Documentation: OpenAPI/Swagger specs
+
+**Endpoints**:
+- `/api/v1/organizations` - Organization management
+- `/api/v1/users` - User management
+- `/api/v1/products` - Product catalog
+- `/api/v1/interactions` - Interaction data
+- `/api/v1/patterns` - Pattern data
+- `/api/v1/analytics` - Analytics and billing
+- `/api/v1/notifications` - User notifications
+
+### 2. GraphQL API (Optional/Future)
+
+**Status**: Not currently implemented. Marked as optional for future optimization.
+
+**Potential Use Case**: Optimized frontend-to-backend communication for dashboard
+
+The REST API currently provides all necessary functionality for the platform. GraphQL could be added in the future if complex nested queries or optimized data fetching becomes critical for performance.
+
+### 3. Agent2Agent (A2A) Protocol
+
+**Audience**: Enterprise AI systems, agent frameworks
+
+**Features**:
+- Standardized Messaging: Agent-to-agent communication protocol
+- Capability Discovery: Dynamic capability negotiation
+- Task Delegation: Multi-agent task coordination
+- Authentication Required: API key or system-level auth
+- Calls MCP Server: Proxies requests to MCP for data access
+
+**Integration**: External agents can call CROW's A2A service to interact with interaction and pattern data.
+
+### 4. MCP Server
+
+**Audience**: LLM applications, Claude, ChatGPT, other AI tools
+
+**Features**:
+- Context Retrieval: Fetch relevant data for LLM context
+- Tool Execution: Execute CROW operations via Interaction and Pattern services
+- Resource Access: Access stored interactions and patterns
+- API Key Required: Authentication via API key
+- Routes Through Gateway: Acts as external party for security
+
+**Implementation**: Built on Cloudflare MCP Workers
+
+**Standard Compliance**: Follows Model Context Protocol specification
+
+**Exposed Services**:
+- Interaction Service (read access)
+- Pattern Service (read access)
+- Query capabilities for LLM context enrichment
+
+## Protocol Summary
+
+| Protocol | Transport | Use Case |
+|----------|-----------|----------|
+| **REST** | HTTPS | Traditional integration, CRUD operations |
+| **Agent2Agent** | JSON-RPC/WSS | AI agent interoperability |
+| **MCP** | Streamable HTTP | LLM assistant integration |
+| **Webhooks** | HTTPS | Event-driven notifications (optional) |
+| **GraphQL** | HTTPS/WSS | Flexible queries, real-time subscriptions (optional) |
+
+## Authentication
+
+### Session-Based Authentication
+
+For dashboard and authenticated user access:
+
+```javascript
+// Session token from Better Auth
+// Stored in frontend, sent with every request
+fetch('/api/v1/organizations', {
+ headers: {
+ 'Cookie': 'session=...'
+ }
+});
+```
+
+- Better Auth with Drizzle ORM
+- Session tokens managed automatically
+- Cookie-based session storage
+- Session validation at API Gateway
+
+### API Key Authentication
+
+For external integrations and SDK usage:
+
+```bash
+curl -X GET https://api.crow.example.com/v1/interactions \
+ -H "Authorization: Bearer YOUR_API_KEY"
+```
+
+**Key Management:**
+- Generated in dashboard Settings > API Keys
+- Configurable expiration
+- Permission-based access (interactions, patterns)
+- Revokable at any time
+- Encrypted at rest
+
+### JWT Tokens (Internal)
+
+API Gateway converts sessions/API keys to JWTs for internal service communication:
+
+- Used between microservices
+- No TTL (optimized for performance)
+- Contains user/org context and permissions
+- Cached mapping (1-5 min) to reduce database calls
+
+## Rate Limiting
+
+Rate limits are enforced per API key or session:
+
+| Tier | Requests/min | Requests/day | Notes |
+|------|-------------|--------------|-------|
+| Public | 10 | 100 | Unauthenticated requests |
+| Free | 60 | 1,000 | Basic tier |
+| Starter | 300 | 50,000 | Standard usage |
+| Professional | 1,000 | 500,000 | High volume |
+| Enterprise | Custom | Custom | Negotiated limits |
+
+**Rate Limit Headers:**
+```
+X-RateLimit-Limit: 60
+X-RateLimit-Remaining: 42
+X-RateLimit-Reset: 1640000000
+```
+
+## Webhooks (Optional/Future)
+
+**Status**: Marked as optional. Not part of core architecture.
+
+**Rationale**: Webhooks add complexity to the platform. Queue-based integrations provide similar functionality with better reliability and control. If webhooks are needed in the future, they can be implemented as an optional add-on.
+
+**Alternative**: Organizations can use polling or the MCP/A2A protocols for real-time integration needs.
+
+## Error Handling
+
+All APIs return consistent error responses:
+
+```json
+{
+ "error": {
+ "code": "VALIDATION_ERROR",
+ "message": "Invalid date format",
+ "details": {
+ "field": "date_from",
+ "expected": "ISO 8601 format"
+ }
+ }
+}
+```
+
+## Related Documentation
+
+- [System Architecture](./system-architecture.md) - Overall platform architecture
+- [Services Architecture](./microservices.md) - Service design
+- [Website Interaction Tracking](../features/website-interaction-tracking.md) - Data ingestion
diff --git a/docs/architecture/microservices.md b/docs/architecture/microservices.md
new file mode 100644
index 0000000..c2cdded
--- /dev/null
+++ b/docs/architecture/microservices.md
@@ -0,0 +1,591 @@
+---
+sidebar_position: 3
+---
+
+# Services Architecture
+
+## Overview
+
+CROW is built on Cloudflare Workers with a TypeScript-based microservices architecture. Each service is a dedicated Worker with specific responsibilities, communicating through mTLS, Cloudflare Queues, and service bindings. All AI work uses Google Gemini models via Vercel AI SDK.
+
+## Service Architecture
+
+```mermaid
+graph TB
+ subgraph "API Gateway"
+ Gateway[API Gateway
mTLS + JWT Issuing]
+ end
+
+ subgraph "Core Services"
+ Auth[Auth Service]
+ User[User Service]
+ Org[Organization Service]
+ Product[Product Service]
+ Notification[Notification Service]
+ Analytics[Analytics Service]
+ end
+
+ subgraph "Data Processing Services"
+ Interaction[Interaction Service]
+ Pattern[Pattern Service]
+ Chat[Chat Service]
+ end
+
+ subgraph "Component Workers"
+ WebIngest[Web Ingest Worker]
+ SocialWorker[Social Worker]
+ CCTVWorker[CCTV Worker]
+ end
+
+ subgraph "External Integration"
+ MCP[MCP Server]
+ A2A[A2A Service]
+ end
+
+ subgraph "Storage"
+ D1[D1 Database]
+ R2[R2 Storage]
+ Vec[Vectorize]
+ Queue[Cloudflare Queues]
+ DO[Durable Objects]
+ end
+
+ Gateway --> Auth
+ Gateway --> Core Services
+ Gateway --> Data Processing Services
+
+ WebIngest --> DO
+ DO --> Queue
+ SocialWorker --> Queue
+ CCTVWorker --> Queue
+
+ Queue --> Interaction
+ Queue --> Pattern
+ Queue --> Analytics
+
+ Interaction --> Vec
+ Pattern --> Vec
+ Org --> Vec
+ Product --> Vec
+
+ MCP --> Gateway
+ A2A --> MCP
+```
+
+## API Gateway
+
+The API Gateway is the single entry point for all client requests, centralizing cross-cutting concerns.
+
+**Purpose**: Request routing, authentication verification, and rate limiting.
+
+**Responsibilities:**
+- Route requests to appropriate backend services
+- Validate sessions and API keys
+- Convert sessions/API keys to JWTs for internal communication
+- Enforce rate limiting per key and per IP
+- Request validation and shaping
+- Add correlation IDs for distributed tracing
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- mTLS for service-to-service communication
+
+**Bindings:**
+- All backend services via mTLS
+- Auth Service for session/key validation
+
+## Core Services
+
+### Auth Service
+
+**Purpose**: Critical service for all authentication and authorization.
+
+**Responsibilities:**
+- Session-based authentication (Better Auth + Drizzle)
+- API key management and validation
+- JWT token issuance for internal services
+- Public request JWT generation (per IP, rate-limited)
+- System-level request authorization
+- Session caching (1-5 min TTL)
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Better Auth library for session management
+- Drizzle ORM for database access
+
+**Bindings:**
+- D1: User sessions, API keys
+- KV: Session cache
+
+### User Service
+
+**Purpose**: User management and profile operations.
+
+**Responsibilities:**
+- User signup, login
+- User profile management
+- Team member references
+- Chat creator tracking
+- Overview page data
+
+**Bindings:**
+- D1: User data
+- Auth Service: Session validation
+
+### Organization Service
+
+**Purpose**: Organization data and context management.
+
+**Responsibilities:**
+- Organization CRUD operations
+- Maintains Vectorize store for organization context
+- Provides context to Interaction and Pattern services
+- Builds organization profiles from usage
+- GDPR-compliant data clearing
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Gemini AI via Vercel AI SDK for context building
+
+**Bindings:**
+- D1: Organization data
+- Vectorize: Organization context embeddings
+
+### Product Service
+
+**Purpose**: Product catalog and web scraping.
+
+**Responsibilities:**
+- Product CRUD operations
+- Web scraping with Cloudflare Browser Rendering
+- Sitemap.xml analysis
+- Product refinement interface
+- Vectorize store for product data
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Gemini AI via Vercel AI SDK for product extraction
+- Cloudflare Browser Rendering for scraping
+
+**Bindings:**
+- D1: Product data
+- Vectorize: Product embeddings
+- Browser Rendering: Web scraping
+
+### Notification Service
+
+**Purpose**: User notification management.
+
+**Responsibilities:**
+- Store notification history
+- Queue-based notification creation
+- Trusted queue messages (no auth)
+- Notification display
+
+**Bindings:**
+- D1: Notifications
+- Queues: Notification events
+
+### Analytics Service
+
+**Purpose**: Usage tracking and billing.
+
+**Responsibilities:**
+- Queue-based event processing
+- Tracks interactions and patterns
+- Usage analytics
+- Billing calculations
+
+**Bindings:**
+- D1: Usage data, billing records
+- Queues: Usage events
+
+## Data Processing Services
+
+### Interaction Service
+
+**Purpose**: Core service for processing any input into insights.
+
+**Responsibilities:**
+- Processes video, images, text from any source
+- Retrieves context from Organization and Product services
+- Generates interaction records with textual descriptions
+- Identifies products involved
+- Exposed via MCP server
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Gemini AI via Vercel AI SDK
+- Cloudflare AI Gateway for LLM routing
+
+**Trigger:** Queue-based (Cloudflare Queues)
+
+**Output:** Interaction records with text, metadata, product associations
+
+**Bindings:**
+- Queues: Input data
+- D1: Metadata
+- R2: Raw data
+- Vectorize: Interaction embeddings
+
+### Pattern Service
+
+**Purpose**: Discovers patterns across interactions.
+
+**Responsibilities:**
+- Cron-triggered daily (last 24 hours)
+- Finds patterns across sessions
+- Aggregates: day, week, month, year, all-time
+- Self-triggers via queues for multi-period aggregation
+- Uses Organization and Product context
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Gemini AI via Vercel AI SDK
+- Cloudflare AI Gateway for LLM routing
+
+**Trigger:** Cron job (daily) + self-triggered queues
+
+**Output:** Pattern records with text, metadata, product associations
+
+**Bindings:**
+- Cron Triggers: Daily execution
+- Queues: Self-triggering
+- D1: Metadata, pattern records
+- Vectorize: Pattern embeddings
+
+### Chat Service (Dashboard BFF)
+
+**Purpose**: Backend for Frontend for dashboard chat.
+
+**Responsibilities:**
+- Chat history management
+- Message storage
+- Artifacts and assets management
+- Multi-agentic orchestration
+- Concurrent agent dispatching
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Gemini AI via Vercel AI SDK
+- Cloudflare AI Gateway for LLM routing
+- Multi-agent system via Vercel AI SDK
+
+**Integration:** Dashboard-specific, not generic
+
+**Bindings:**
+- D1: Chat history
+- R2: Artifacts, assets
+- Vectorize: Semantic search
+- Interaction/Pattern Services: Data access
+
+## Component Workers
+
+### Web Ingest Worker
+
+**Purpose**: Receive events from JavaScript SDK and manage web sessions.
+
+**Responsibilities:**
+- Event validation and transformation
+- API Gateway routing
+- Session management via Durable Objects
+- Hourly inactivity trigger (1 hour = session end)
+- Queue dispatch to Interaction Service
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Durable Objects for session state
+
+**Bindings:**
+- Durable Objects: Session state with alarm
+- Queues: Session processing
+- D1: Temporary event storage
+
+**Session Definition:** 1 hour of user inactivity triggers session processing.
+
+### Social Worker
+
+**Purpose**: Scrape social media data via cron jobs.
+
+**Responsibilities:**
+- **AI-generated web search**: Generate queries, search, extract unique links
+- **Social media scraping**: Use provided links to fetch content
+- Web extraction for all discovered content
+- Duplicate detection
+- Queue dispatch to Interaction Service
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Gemini AI via Vercel AI SDK for query generation
+- Cloudflare Browser Rendering for web extraction
+
+**Trigger:** Cron-based scheduled execution
+
+**Bindings:**
+- Cron Triggers: Scheduled execution
+- D1: Scrape state, seen links
+- Queues: Extracted content
+- Browser Rendering: Web scraping
+
+**Session Definition:** One cron job trigger = one session.
+
+### CCTV Worker
+
+**Purpose**: Handle CCTV video streaming and processing.
+
+**Responsibilities:**
+- Receive WebRTC streams via Cloudflare Realtime SFU
+- Convert WebRTC to WebSocket
+- Forward to Gemini Live API
+- Hourly session creation
+- Queue dispatch to Interaction Service
+
+**Technology:**
+- TypeScript/Bash on device and Cloudflare Workers
+- Cloudflare Realtime SFU for WebRTC
+- WebRTC-to-WebSocket adapter
+- Gemini Live API for real-time analysis
+
+**Deployment:**
+- Background daemon on CCTV server
+- Starts on system startup
+- Bash script for initial setup
+
+**Trigger:** Continuous streaming with hourly sessions
+
+**Bindings:**
+- Realtime SFU: WebRTC streams
+- Queues: Hourly session data
+- Gemini Live: Video analysis
+
+**Session Definition:** 1 hour of continuous footage = one session.
+
+## External Integration Services
+
+### MCP Server
+
+**Purpose**: Model Context Protocol server for LLM integrations.
+
+**Responsibilities:**
+- Exposes Interaction and Pattern services
+- API key authentication
+- Routes through API Gateway as external party
+- Standard MCP protocol compliance
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+- Built on Cloudflare MCP Workers
+- MCP protocol specification
+
+**Integrations:**
+- ChatGPT, Claude, other LLMs
+- Developer tools
+- External AI agents
+
+**Bindings:**
+- API Gateway: External auth
+- Interaction Service: Data access
+- Pattern Service: Data access
+
+### A2A Service
+
+**Purpose**: Agent-to-agent communication protocol.
+
+**Responsibilities:**
+- Calls MCP Server for data
+- Agent communication protocol
+- Authentication required
+- Enterprise AI integrations
+
+**Technology:**
+- TypeScript on Cloudflare Workers
+
+**Bindings:**
+- MCP Server: Data access
+- Auth Service: Authentication
+
+## Service Communication
+
+### mTLS (Mutual TLS)
+
+Services communicate via mTLS for secure bidirectional verification:
+
+- API Gateway configured to trust internal services
+- Each service validates calling service
+- Additional verification layer beyond mTLS
+- Prevents vendor lock-in (alternative to Service Bindings)
+
+### JWT Tokens
+
+API Gateway issues JWTs for internal communication:
+
+```javascript
+// API Gateway converts session/API key to JWT
+const jwt = await issueJWT({
+ userId: session.userId,
+ orgId: session.orgId,
+ permissions: session.permissions
+});
+
+// Services validate JWT
+const decoded = await validateJWT(request.headers.get('Authorization'));
+```
+
+**JWT Characteristics:**
+- No TTL/expiration (performance optimization)
+- Contains user, org, permissions
+- Cached mapping (1-5 min TTL)
+- Optimized for high-volume data workloads
+
+### Queue-based Communication
+
+Asynchronous communication via Cloudflare Queues:
+
+```javascript
+// Producer (Web Ingest Worker)
+await env.INTERACTION_QUEUE.send({
+ type: 'web_session',
+ sessionId: '...',
+ events: [...],
+ orgId: '...'
+});
+
+// Consumer (Interaction Service)
+export default {
+ async queue(batch, env) {
+ for (const message of batch.messages) {
+ await processInteraction(message.body, env);
+ }
+ }
+};
+```
+
+### Service Bindings (Limited Use)
+
+While Cloudflare Service Bindings exist, CROW primarily uses mTLS to avoid vendor lock-in. Service Bindings may be used for specific internal-only services where portability is not a concern.
+
+## Technology Stack
+
+| Service Type | Language | AI Framework | Key Libraries |
+|-------------|----------|--------------|---------------|
+| All Services | TypeScript | Vercel AI SDK | Hono, Drizzle ORM |
+| AI Processing | TypeScript | Gemini models | Cloudflare AI Gateway |
+| Web Scraping | TypeScript | Gemini models | Browser Rendering |
+| Auth | TypeScript | N/A | Better Auth |
+
+**Note on Hono**: Hono is a lightweight, fast web framework used across all CROW microservices. It provides routing, middleware, and request handling optimized for Cloudflare Workers.
+
+### Programming Language Selection
+
+| Language | Use Case | Justification |
+|----------|----------|---------------|
+| **TypeScript** | All core services on Cloudflare Workers | Native Worker support, strong ecosystem, type safety |
+| **Python** | AI/ML services (if needed) | Strong ML tooling, useful for experiments |
+| **Go** | Container-based services (future) | High performance, good concurrency |
+
+**Note**: TypeScript is the primary language. Python services may be required if AI libraries lack TypeScript support. Go remains a future option if container-based services become necessary.
+
+## Repository Naming Conventions
+
+- **Core APIs**: `organization-service`, `user-service`, `product-service`, `auth-service`
+- **Component Workers**: `web-ingest-worker`, `social-worker`, `cctv-worker`
+- **Processing Services**: `interaction-service`, `pattern-service`, `chat-service`
+- **Integration**: `mcp-server`, `a2a-service`
+- **Clients**: `landing-client`, `auth-client`, `dashboard-client`
+
+## Deployment
+
+### Wrangler Configuration
+
+Each service has its own `wrangler.toml`:
+
+```toml
+name = "crow-interaction-service"
+main = "src/index.ts"
+compatibility_date = "2024-01-01"
+
+[[d1_databases]]
+binding = "DB"
+database_id = "..."
+
+[[r2_buckets]]
+binding = "STORAGE"
+bucket_name = "crow-storage"
+
+[[vectorize]]
+binding = "VECTORIZE"
+index_name = "interaction-embeddings"
+
+[[queues.consumers]]
+queue = "interaction-queue"
+max_batch_size = 10
+max_retries = 3
+
+[ai]
+binding = "AI"
+```
+
+### Local Development
+
+- **Kubernetes with Kind**: Docker-based local environment
+- **Consistency**: Same config for local and production
+- **Future-ready**: Enables cloud migration if needed
+
+### CI/CD Pipeline
+
+```mermaid
+flowchart LR
+ Code["Code Push"] --> Lint["Lint & Type Check"]
+ Lint --> Test["Run Tests"]
+ Test --> Preview["Preview Deploy"]
+ Preview --> Approve["Manual Approval"]
+ Approve --> Prod["Production Deploy"]
+ Prod --> Notify["Slack Notification"]
+```
+
+#### Pipeline Stages
+
+| Stage | Action |
+|-------|--------|
+| **Lint** | ESLint, Prettier, TypeScript checking |
+| **Test** | Bun test runner with coverage reporting |
+| **Deploy Dev** | Staging deployment on pull requests |
+| **Deploy Prod** | Production deployment on main branch merge |
+| **Notify** | Slack notifications for deployment status |
+
+Deployments use Wrangler CLI for Workers and Containers with environment-specific configuration managed through Cloudflare's secrets store.
+
+## Observability and Monitoring
+
+### Metrics Collection
+
+Cloudflare Analytics Engine provides edge-native metrics collection without impacting request latency:
+
+- Request volumes and throughput
+- Latency distributions (p50, p95, p99)
+- Error rates by service
+- AI processing times
+
+### Logging
+
+Structured logs stream to Axiom for centralized analysis:
+
+- **Debugging**: Trace requests across services
+- **Audit trails**: Compliance and access logging
+- **Performance analysis**: Identify bottlenecks
+- **Long-term retention**: Historical analysis
+
+### Alerting
+
+- Real-time alerts on error rate thresholds
+- Latency degradation notifications
+- Queue depth monitoring
+- AI Gateway usage alerts
+
+## Related Documentation
+
+- [System Architecture](./system-architecture.md) - Overall platform architecture
+- [Integration API](./integration-api.md) - API details
+- [Data Storage Architecture](./data-lake-architecture.md) - Storage design
+- [Frontend Architecture](./frontend-architecture.md) - Client applications
+- [User Permission Levels](../reference/user-permissions.md) - Access control
diff --git a/docs/architecture/system-architecture.md b/docs/architecture/system-architecture.md
new file mode 100644
index 0000000..67bb2e8
--- /dev/null
+++ b/docs/architecture/system-architecture.md
@@ -0,0 +1,873 @@
+---
+sidebar_position: 1
+---
+
+# System Architecture
+
+## Overview
+
+CROW is a data platform that gathers human-product interactions for brand-owned companies. We collect raw data from three primary channels—website interactions, CCTV footage, and social media—analyze these interactions with context, and find patterns within them. Built entirely on Cloudflare's edge infrastructure with Gemini AI models, the platform ensures low-latency global distribution and simplified operations.
+
+### Phased Rollout Strategy
+
+CROW's three components are being built in phases:
+
+- **Phase 1 (Current)**: Web component - Foundation for all core microservices
+- **Phase 2**: Social component - Leverages existing infrastructure
+- **Phase 3**: CCTV component - Most advanced, requires additional infrastructure knowledge
+
+This phased approach allows us to establish a complete end-to-end service with the Web component first, then rapidly integrate additional components as the core infrastructure stabilizes.
+
+### Architectural Layers
+
+CROW employs an event-driven microservices architecture organized into five logical layers:
+
+| Layer | Components | Responsibility |
+| ----------------- | -------------------------------------- | -------------------------------------- |
+| **Presentation** | Dashboard, Landing, Auth clients, SDKs | User interfaces and data emission |
+| **API Gateway** | Gateway Worker | Authentication, routing, rate limiting |
+| **Ingestion** | Web, Social, CCTV workers | Channel-specific data capture |
+| **Core Services** | Interaction, Pattern, Product, etc. | Business logic and AI processing |
+| **Storage** | D1, R2, Vectorize, Queues | Persistent state and messaging |
+
+This separation enables independent scaling—ingestion spikes don't affect query performance, and each layer can evolve independently.
+
+The following diagram illustrates the high-level system architecture:
+
+```mermaid
+flowchart TB
+ subgraph Channels["Data Channels"]
+ WEB["Website Interactions"]
+ CCTV["CCTV Footage"]
+ SOCIAL["Social Media"]
+ end
+
+ subgraph Edge["Cloudflare Edge"]
+ SDK["JavaScript SDK"]
+ REALTIME["Realtime SFU"]
+ CRON["Cron Triggers"]
+ end
+
+ subgraph Processing["Processing Layer"]
+ QUEUE["Queues"]
+ TRIGGER["Trigger Service"]
+ WORKFLOWS["Workflows"]
+ end
+
+ subgraph Services["Core Services"]
+ INTERACTION["Interaction Service"]
+ PATTERN["Pattern Service"]
+ PRODUCT["Product Service"]
+ end
+
+ subgraph Storage["Data Storage"]
+ D1["D1 Database"]
+ R2["R2 Object Storage"]
+ VECTORIZE["Vectorize"]
+ end
+
+ subgraph APIs["API Layer"]
+ REST["REST API"]
+ A2A["Agent2Agent"]
+ MCP["MCP Server"]
+ end
+
+ WEB --> SDK
+ SDK --> D1
+ CCTV --> REALTIME
+ REALTIME --> R2
+ SOCIAL --> CRON
+ CRON --> QUEUE
+
+ D1 --> QUEUE
+ R2 --> QUEUE
+ QUEUE --> TRIGGER
+ TRIGGER --> WORKFLOWS
+ WORKFLOWS --> INTERACTION
+ WORKFLOWS --> PATTERN
+ INTERACTION --> VECTORIZE
+ PATTERN --> VECTORIZE
+
+ PRODUCT --> VECTORIZE
+
+ Storage --> APIs
+```
+
+## Platform Infrastructure
+
+### Cloudflare Edge Platform
+
+The entire CROW platform is built on Cloudflare's edge infrastructure, providing:
+
+- **Global Distribution**: 300+ data centers worldwide
+- **Low Latency**: Sub-50ms response times globally
+- **Simplified Operations**: No server management required
+- **Integrated Services**: Seamless connectivity between all components
+
+### Core Infrastructure Components
+
+| Component | Cloudflare Service | Purpose |
+| ------------------- | ------------------ | -------------------------------- |
+| **Compute** | Workers | Serverless edge compute |
+| **Database** | D1 | SQLite-based relational database |
+| **Object Storage** | R2 | S3-compatible blob storage |
+| **Vector Database** | Vectorize | AI embedding storage and search |
+| **Message Queue** | Queues | Async message processing |
+| **Orchestration** | Workflows | Complex multi-step processing |
+| **Real-time** | Realtime SFU | WebRTC-based video streaming |
+| **Scheduling** | Cron Triggers | Scheduled task execution |
+
+## Data Channels
+
+CROW ingests data from three primary channels, each with dedicated processing pipelines.
+
+### Website Interactions
+
+Website interactions are captured via a lightweight JavaScript SDK that can be deployed on web, mobile (React Native), and desktop (Electron) applications.
+
+```mermaid
+flowchart LR
+ subgraph Client["Client Application"]
+ SDK["CROW SDK"]
+ Events["User Events"]
+ end
+
+ subgraph Edge["Cloudflare Edge"]
+ Gateway["API Gateway"]
+ Ingest["Web Ingest Worker"]
+ DO["Durable Object"]
+ end
+
+ subgraph Processing["Processing"]
+ Queue["Interaction Queue"]
+ end
+
+ Events --> SDK
+ SDK --> Gateway
+ Gateway --> Ingest
+ Ingest --> DO
+ DO -- "After 1hr inactivity" --> Queue
+```
+
+**Key Features:**
+
+- Lightweight SDK for web, mobile (React Native), and desktop (Electron)
+- Automatic event batching
+- Session management via Durable Objects
+- Hourly inactivity trigger (sessions without activity for 1 hour are processed)
+- Privacy-first design
+- Real-time event streaming through API Gateway
+
+**Session Definition:** A web session is defined as a period of user activity, ending after 1 hour of inactivity. At this point, the session is sent to the Interaction Service for processing.
+
+**[→ Learn more about Website Interaction Tracking](../features/website-interaction-tracking.md)**
+
+### CCTV Footage
+
+The CCTV component streams real-time video from retail stores through Cloudflare's Realtime serverless SFU, converting WebRTC streams to WebSocket and feeding them to Gemini Live for analysis.
+
+```mermaid
+flowchart LR
+ subgraph Store["Retail Store"]
+ CCTV["CCTV Camera"]
+ Daemon["Background Daemon"]
+ end
+
+ subgraph Cloudflare["Cloudflare"]
+ SFU["Realtime SFU"]
+ Adapter["WebRTC to WebSocket"]
+ end
+
+ subgraph AI["Google AI"]
+ Gemini["Gemini Live"]
+ end
+
+ subgraph Processing["Processing"]
+ Queue["Interaction Queue"]
+ end
+
+ CCTV --> Daemon
+ Daemon --> SFU
+ SFU --> Adapter
+ Adapter --> Gemini
+ Gemini --> Queue
+```
+
+**Key Features:**
+
+- WebRTC-based low-latency streaming via Cloudflare Realtime SFU
+- WebRTC-to-WebSocket adapter for Gemini Live integration
+- Real-time video analysis with Gemini Live API
+- Hourly session segmentation (each hour = one session)
+- Background daemon streams on system startup
+- Multi-stream combination into single high-resolution view
+- Privacy compliance with configurable camera selection
+
+**Session Definition:** A CCTV session is defined as one hour of continuous footage, after which a new session begins.
+
+### Social Media
+
+Scheduled scraping of public social media data using Cron Triggers with two distinct approaches.
+
+```mermaid
+flowchart LR
+ subgraph Triggers["Cron Jobs"]
+ WebSearch["AI-Generated Web Searches"]
+ SocialLinks["Social Media Link Scraping"]
+ end
+
+ subgraph Sources["Social Platforms"]
+ Web["Web Search Results"]
+ Social["Social Media Accounts"]
+ end
+
+ subgraph Processing["Processing"]
+ Extract["Web Extraction"]
+ Queue["Interaction Queue"]
+ end
+
+ WebSearch --> Web
+ SocialLinks --> Social
+ Web --> Extract
+ Social --> Extract
+ Extract --> Queue
+```
+
+**Key Features:**
+
+- **AI-driven web search**: Generates queries, searches, extracts unique links, performs web extraction
+- **Social media scraping**: Uses provided social media links from organization setup to fetch relevant content
+- Cron-based scheduled execution
+- Duplicate detection for unique links
+- Platform-specific adapters
+- Web extraction for all discovered content
+
+**Session Definition:** A social media session is defined as a single cron job trigger execution. Each cron run processes and analyzes content as one session.
+
+## Processing Layer
+
+### Cloudflare Queues
+
+All incoming data flows through Cloudflare Queues for reliable, ordered processing.
+
+**Queue Architecture:**
+
+- **interaction-queue**: Website events and processed CCTV frames
+- **social-queue**: Social media mentions
+- **processing-queue**: AI processing tasks
+- **export-queue**: Report generation tasks
+
+### Trigger Service
+
+A dedicated Worker that monitors queues and initiates appropriate Workflows.
+
+```javascript
+// Simplified trigger logic
+export default {
+ async queue(batch, env) {
+ for (const message of batch.messages) {
+ const { type, data } = message.body;
+
+ switch (type) {
+ case 'interaction':
+ await env.WORKFLOW.create('process-interaction', data);
+ break;
+ case 'social':
+ await env.WORKFLOW.create('analyze-social', data);
+ break;
+ case 'cctv':
+ await env.WORKFLOW.create('process-video', data);
+ break;
+ }
+ }
+ },
+};
+```
+
+### Cloudflare Workflows
+
+Complex, multi-step processing is orchestrated via Cloudflare Workflows.
+
+```mermaid
+flowchart TD
+ subgraph Workflow["Processing Workflow"]
+ Start["Receive Data"]
+ Validate["Validate Input"]
+ Enrich["Enrich Context"]
+ AI["AI Processing"]
+ Store["Store Results"]
+ Notify["Notify Downstream"]
+ end
+
+ Start --> Validate
+ Validate --> Enrich
+ Enrich --> AI
+ AI --> Store
+ Store --> Notify
+```
+
+**Key Workflows:**
+
+- `process-interaction`: Handle website events
+- `analyze-social`: Process social media mentions
+- `process-video`: Analyze CCTV footage
+- `generate-insights`: Create aggregated insights
+- `export-report`: Generate exportable reports
+
+## Core Services
+
+CROW's microservices architecture is built on TypeScript and Cloudflare Workers, with each service handling specific responsibilities.
+
+### Interaction Service
+
+**Purpose**: Core service that processes any input (video, images, text) and generates meaningful insights.
+
+**Responsibilities:**
+
+- Takes input from any source (web, CCTV, social media)
+- Retrieves context from Organization and Product services
+- Generates interaction records with textual descriptions
+- Identifies products involved in each interaction
+- Exposes functionality via MCP server for external use
+- Uses Gemini AI models via Vercel AI SDK
+
+**Trigger:** Entirely queue-based (Cloudflare Queues)
+
+**Output:** Interaction records with text, metadata, and product associations
+
+### Pattern Service
+
+**Purpose**: Discovers patterns across interactions over different time periods.
+
+**Responsibilities:**
+
+- Cron-triggered daily (processes last 24 hours of interactions)
+- Finds patterns across sessions within time periods
+- Aggregates patterns for: day, week, month, year, all-time
+- Self-triggers via queues for multi-period aggregation
+- Uses Organization and Product context for analysis
+- Uses Gemini AI models via Vercel AI SDK
+
+**Trigger:** Cron job (daily) + self-triggered queues
+
+**Output:** Pattern records with text, metadata, and product associations
+
+### Chat Service (Dashboard)
+
+**Purpose**: BFF (Backend for Frontend) service for the chat application in the dashboard.
+
+**Responsibilities:**
+
+- Manages chat history and messages
+- Maintains conversation context
+- Handles chat-related assets and artifacts
+- Multi-agentic AI system for querying data
+- Provides conversational interface to all platform data
+- Uses Gemini AI models via Vercel AI SDK
+
+**Integration:** Dashboard-specific, not a generic reusable service
+
+**[→ Learn more about Chat System](../features/chat-system.md)**
+
+### Organization Service
+
+**Purpose**: Manages organization data and context.
+
+**Responsibilities:**
+
+- Stores organization details and settings
+- Maintains Vectorize vector store for organization context
+- Provides context to Interaction and Pattern services
+- Builds organization profiles based on CROW usage
+- GDPR-compliant data clearing from settings page
+
+### User Service
+
+**Purpose**: Handles all user-related operations.
+
+**Responsibilities:**
+
+- User signup, login, and authentication
+- User profile management
+- Team member references
+- Chat creator tracking
+- Overview page data aggregation
+
+### Notification Service
+
+**Purpose**: Manages all user notifications.
+
+**Responsibilities:**
+
+- Stores notification history per user
+- Queue-based notification creation
+- Trusted queue messages (no auth required)
+- Notification display and management
+
+### Auth Service
+
+**Purpose**: Critical service handling all authentication and authorization.
+
+**Responsibilities:**
+
+- Session-based authentication with Better Auth
+- API key management and validation
+- JWT token issuance for internal communication
+- Public request JWT generation (per IP, rate-limited)
+- System-level request authorization
+- User session caching (1-5 min TTL)
+
+**[→ Learn more about Authentication](#authentication)**
+
+### Product Service
+
+**Purpose**: Product catalog management and web scraping.
+
+**Responsibilities:**
+
+- Product CRUD operations
+- Web scraping with Cloudflare Browser Rendering
+- Sitemap.xml analysis for context
+- Product data refinement
+- Maintains Vectorize store for product data
+- Uses Gemini AI models via Vercel AI SDK
+
+**[→ Learn more about Product Scraping](../features/product-scraping.md)**
+
+### Analytics Service
+
+**Purpose**: Usage tracking, billing, and analytics.
+
+**Responsibilities:**
+
+- Queue-based event processing
+- Tracks interactions and patterns for billing
+- Usage analytics and reporting
+- Billing calculations (per interaction/pattern pricing)
+
+### MCP Server
+
+**Purpose**: Public MCP (Model Context Protocol) server for external integrations.
+
+**Responsibilities:**
+
+- Exposes Interaction and Pattern services via MCP standard
+- Requires API key authentication
+- Routes through API Gateway as external party
+- Enables ChatGPT, Claude, and other LLM integrations
+- Built on Cloudflare MCP Workers
+
+### A2A (Agent-to-Agent)
+
+**Purpose**: External agent communication service.
+
+**Responsibilities:**
+
+- Calls MCP Server for data access
+- Provides agent-to-agent communication protocol
+- Requires authentication
+- Enables enterprise AI agent integrations
+
+## Data Storage
+
+### D1 Database
+
+Primary relational database for structured data.
+
+**Schema Overview:**
+
+- Organizations, Users, API Keys
+- Products and Categories
+- Interaction metadata
+- Processing jobs and status
+- Configuration and settings
+
+**Key Features:**
+
+- SQLite compatibility
+- Automatic replication
+- Point-in-time recovery
+- Global read distribution
+
+### R2 Object Storage
+
+S3-compatible storage for binary data and archives.
+
+**Storage Buckets:**
+
+- `raw-interactions`: Original event data
+- `cctv-frames`: Video frame extracts
+- `exports`: Generated reports
+- `assets`: Static assets
+
+**Key Features:**
+
+- Zero egress fees
+- S3 API compatibility
+- Lifecycle policies
+- Automatic CDN integration
+
+### Vectorize
+
+AI-native vector database for semantic search.
+
+**Vector Indexes:**
+
+- `interaction-embeddings`: Interaction text embeddings
+- `product-embeddings`: Product description embeddings
+- `social-embeddings`: Social media content embeddings
+
+**Key Features:**
+
+- High-dimensional vector storage
+- Fast similarity search
+- Metadata filtering
+- Automatic index optimization
+
+**[→ Learn more about Data Lake Architecture](./data-lake-architecture.md)**
+
+## API Layer
+
+### REST API
+
+Standard RESTful endpoints for CRUD operations.
+
+**Endpoint Groups:**
+
+- `/api/v1/organizations` - Organization management
+- `/api/v1/products` - Product catalog
+- `/api/v1/interactions` - Interaction data
+- `/api/v1/insights` - Generated insights
+- `/api/v1/exports` - Export management
+
+### GraphQL API (Optional/Future)
+
+**Status**: Not currently implemented, potential future optimization.
+
+GraphQL support could be added for optimized frontend-service communication, but is not part of the current architecture. The REST API provides all necessary functionality.
+
+### Agent2Agent (A2A) Protocol
+
+Enterprise integration for AI agent communication.
+
+**Capabilities:**
+
+- Standardized agent messaging
+- Capability discovery
+- Task delegation
+- Result aggregation
+- Authentication required
+
+### MCP Server
+
+Model Context Protocol server for LLM integrations.
+
+**Supported Operations:**
+
+- Data retrieval for context
+- Tool execution via Interaction and Pattern services
+- Resource access with API key authentication
+- ChatGPT, Claude, and other LLM tool integrations
+
+**[→ Learn more about Integration API](./integration-api.md)**
+
+## Authentication
+
+CROW employs a multi-layered authentication strategy optimized for security and performance.
+
+### Service-to-Service Authentication (mTLS)
+
+**Purpose**: Secure communication between internal services.
+
+**Implementation:**
+
+- Mutual TLS (mTLS) for bidirectional service verification
+- Natively supported by Cloudflare Workers
+- API Gateway and services configured for mutual trust
+- Additional verification layer beyond mTLS for defense in depth
+
+**Rationale**: While Cloudflare Service Bindings exist, mTLS provides platform independence and prevents vendor lock-in.
+
+### Session-Based Authentication
+
+**Purpose**: User authentication for frontend applications.
+
+**Implementation:**
+
+- Better Auth library with Drizzle ORM integration
+- Session tokens stored in frontend
+- Token sent with every request
+- Initialized in auth client, passed to dashboard client
+- Cookie caching in Better Auth for optimization
+
+### JWT Tokens
+
+**Purpose**: Efficient inter-service communication without database lookups.
+
+**Implementation:**
+
+- API Gateway converts sessions/API keys to JWTs
+- JWTs used for service-to-service calls
+- No TTL/expiration (unrevokable by design)
+- Optimized for speed at scale
+- Prioritizes performance over revocability for data workloads
+
+**Signing Standards:**
+
+- **System JWT**: HS256 with shared secret
+- **User JWT**: RS256 via JWKS from Better Auth
+
+**Caching Strategy:**
+
+- Session/API key to JWT mapping cached (1-5 min TTL)
+- Minimizes database calls for high-frequency operations
+- Drizzle-level caching + Better Auth cookie caching
+
+### Public Requests
+
+**Purpose**: Unauthenticated access to public features (e.g., public chat).
+
+**Implementation:**
+
+- JWT issued per IP address
+- Heavily rate-limited
+- Reused across requests from same IP
+- Automatic JWT generation for public endpoints
+
+### System Requests
+
+**Purpose**: Internal system operations and event-driven workflows.
+
+**Implementation:**
+
+- Specific system-level access permissions
+- Event-driven queue-based communication
+- Trusted internal service authentication
+- Restricted to specific operations
+
+### API Keys
+
+**Purpose**: External client authentication.
+
+**Features:**
+
+- Organization-scoped keys
+- Configurable expiration
+- Revokable through dashboard
+- Permission-based access control
+- Managed by Auth Service
+
+## Frontend Architecture
+
+### Split Application Design
+
+Three separate frontend clients optimized for their specific purposes, designed as building blocks that can be placed in any order.
+
+```mermaid
+flowchart TB
+ subgraph Landing["Landing Client"]
+ Marketing["Marketing Pages"]
+ Pricing["Pricing"]
+ Docs["Documentation"]
+ end
+
+ subgraph Auth["Auth Client"]
+ Signup["Sign Up"]
+ Login["Login"]
+ AuthFlow["Authentication Flows"]
+ end
+
+ subgraph Dashboard["Dashboard Client"]
+ Overview["Overview"]
+ Analytics["Analytics"]
+ Chat["Chat Interface"]
+ Settings["Settings"]
+ end
+
+ Landing --> Auth
+ Auth --> Dashboard
+```
+
+**Landing Client:**
+
+- Public-facing marketing and information
+- SEO optimized
+- Fast initial load
+- Separate from authentication
+
+**Auth Client:**
+
+- Dedicated authentication application
+- Sign up and login flows
+- Session initialization
+- Passed to dashboard client
+
+**Dashboard Client:**
+
+- React SPA
+- Real-time updates
+- Rich interactivity
+- Complex visualizations
+
+**Rationale for Split Design:**
+
+- Building block approach - clients can be rearranged as needed
+- Future flexibility (e.g., mobile/desktop home page different from landing)
+- Better SEO split across different pages
+- Enables different tech stacks per client if needed
+- Cleaner separation of concerns
+
+**[→ Learn more about Frontend Architecture](./frontend-architecture.md)**
+
+## Security & Compliance
+
+### Authentication
+
+- **Session-Based Auth**: Better Auth with Drizzle ORM
+- **API Keys**: Machine-to-machine access with expiration
+- **JWT Tokens**: Internal service communication (no TTL)
+- **mTLS**: Service-to-service mutual verification
+
+### Authorization
+
+- **Permission Levels**: Granular access control (see User Permission Levels)
+- **Organization Scoping**: 1:1 user-organization mapping
+- **API Rate Limiting**: Abuse prevention
+- **Audit Logging**: Compliance tracking
+
+### Data Protection
+
+- **Encryption at Rest**: All storage encrypted
+- **Encryption in Transit**: TLS 1.3 everywhere
+- **Data Residency**: Regional data storage options
+- **GDPR Compliance**: Privacy by design
+
+## Deployment & Operations
+
+### CI/CD Pipeline
+
+```mermaid
+flowchart LR
+ Code["Code Push"] --> Build["Build"]
+ Build --> Test["Test"]
+ Test --> Preview["Preview Deploy"]
+ Preview --> Approve["Manual Approval"]
+ Approve --> Prod["Production Deploy"]
+```
+
+### Monitoring & Observability
+
+- **Cloudflare Analytics**: Built-in metrics
+- **Worker Logs**: Structured logging
+- **Error Tracking**: Automatic error capture
+- **Performance Monitoring**: Real-time latency tracking
+
+### Disaster Recovery
+
+- **Multi-region Replication**: Automatic data replication
+- **Point-in-time Recovery**: D1 database backups
+- **Failover**: Automatic traffic rerouting
+- **Incident Response**: Defined runbooks
+
+## Technology Stack Summary
+
+| Category | Technology | Purpose |
+| ----------------------- | ---------------------------- | ------------------------------------------------------ |
+| **Edge Compute** | Cloudflare Workers | Serverless functions |
+| **Container Runtime** | Workers Containers | Python workloads requiring longer execution |
+| **Database** | Cloudflare D1 | Relational data |
+| **Object Storage** | Cloudflare R2 | Binary data & archives |
+| **Vector DB** | Cloudflare Vectorize | AI embeddings |
+| **Queues** | Cloudflare Queues | Message passing |
+| **Workflows** | Cloudflare Workflows | Orchestration |
+| **Real-time** | Cloudflare Realtime SFU | Video streaming (CCTV) |
+| **Browser Rendering** | Cloudflare Browser Rendering | Web scraping |
+| **Durable Objects** | Cloudflare Durable Objects | Session state management |
+| **AI Gateway** | Cloudflare AI Gateway | LLM request routing |
+| **Frontend** | React + Next.js | User interfaces |
+| **Language** | TypeScript | Services and frontend |
+| **Agent Framework** | Vercel AI SDK | AI orchestration (chat, dashboard) |
+| **Agent Orchestration** | Multi-agent patterns | Advanced workflows (product extraction, social search) |
+| **AI Models** | Google Gemini | All AI processing |
+| **Auth Library** | Better Auth | Session management |
+| **ORM** | Drizzle | Database queries |
+| **API** | REST + MCP + A2A | Data access |
+| **Local Dev** | Kubernetes (Kind) | Docker-based local env |
+
+## Key Architectural Decisions
+
+### Gemini Model Usage
+
+All AI processing in CROW uses Google Gemini models exclusively:
+
+- **High volume support**: Handles large amounts of interaction data
+- **Large context windows**: Processes extensive contextual information
+- **Gemini Live API**: Used for CCTV real-time video analysis
+- **Vercel AI SDK**: Agent framework for all Gemini interactions
+
+#### Model Selection
+
+| Model | Use Case | Capabilities |
+| --------------------- | -------------------------------------- | -------------------------------------------- |
+| **Gemini Pro** | General processing, insight generation | 1M token context, multimodal reasoning |
+| **Gemini Deep Think** | Complex analysis, trend identification | Enhanced reasoning, longer chains of thought |
+| **Gemini Live** | CCTV streaming analysis | Real-time multimodal streaming |
+
+### Cloudflare AI Gateway
+
+All LLM requests route through Cloudflare AI Gateway for centralized management:
+
+| Feature | Benefit |
+| -------------------- | ------------------------------------- |
+| **Request caching** | Reduces redundant API calls and costs |
+| **Rate limiting** | Prevents budget overruns |
+| **Fallback routing** | Automatic failover between providers |
+| **Analytics** | Usage tracking and cost monitoring |
+
+### Organization:User (1:1) Mapping
+
+CROW maintains a strict 1:1 relationship between users and organizations:
+
+- Users must have an organization-based email
+- Simplifies authorization and data scoping
+- Each user belongs to exactly one organization
+- Invited users join the same organization
+- **Critical constraint**: Changing this requires significant architectural refactoring
+
+### Sessions Concept
+
+Sessions define processing boundaries for each component:
+
+- **Web**: User inactivity for 1 hour triggers session processing
+- **CCTV**: 1 hour of continuous footage = one session
+- **Social**: One cron job execution = one session
+
+### Repository Naming Conventions
+
+- **Core APIs**: `organization-service`, `user-service`, `product-service`
+- **Component Workers**: `web-ingest-worker`, `cctv-worker`, `social-worker`
+- **Services**: Named with `-service` suffix
+- **Clients**: Named with `-client` suffix
+
+### Local Development
+
+- **Kubernetes with Kind**: Docker-based local development environment
+- **Future cloud deployment**: K8s setup enables cloud migration if needed
+- **Consistency**: Same configuration for local and production (Cloudflare)
+
+### Optional/Future Features
+
+- **GraphQL**: Not currently implemented, marked as optional future optimization
+- **Webhooks**: Marked as optional, not part of core architecture
+- **Python services**: May be required for AI libraries lacking TypeScript support
+
+## Related Documentation
+
+- **[Frontend Architecture](./frontend-architecture.md)** - UI design and deployment
+- **[Data Lake Architecture](./data-lake-architecture.md)** - Storage design
+- **[Integration API](./integration-api.md)** - API design and protocols
+- **[Services Architecture](./microservices.md)** - Service architecture
+- **[Website Interaction Tracking](../features/website-interaction-tracking.md)** - SDK and ingestion
+- **[Product Scraping](../features/product-scraping.md)** - AI-powered scraping
+- **[Chat System](../features/chat-system.md)** - Conversational interface
+- **[User Signup Flow](../features/user-signup-flow.md)** - Onboarding process
diff --git a/docs/features/_category_.json b/docs/features/_category_.json
new file mode 100644
index 0000000..c7bde35
--- /dev/null
+++ b/docs/features/_category_.json
@@ -0,0 +1,5 @@
+{
+ "label": "Features",
+ "position": 3,
+ "collapsed": false
+}
diff --git a/docs/features/cctv-component.md b/docs/features/cctv-component.md
new file mode 100644
index 0000000..1678a1d
--- /dev/null
+++ b/docs/features/cctv-component.md
@@ -0,0 +1,372 @@
+---
+sidebar_position: 6
+---
+
+# CCTV Component
+
+## Overview
+
+The CCTV component is CROW's most advanced offering, representing **Phase 3** of the rollout. It streams real-time CCTV footage from retail stores, analyzes it using Gemini Live, and generates insights about customer movements, behaviors, and product interactions in physical spaces.
+
+## Why CCTV is Phase 3
+
+The CCTV component requires significant infrastructure knowledge and setup:
+- Real-time video streaming architecture
+- WebRTC/WebSocket conversion
+- Gemini Live API integration
+- Background daemon development for CCTV servers
+- Privacy and compliance considerations
+- High bandwidth and processing requirements
+
+It's deployed after Web and Social components to leverage the established core infrastructure and services.
+
+## Architecture
+
+```mermaid
+flowchart TB
+ subgraph Store["Retail Store"]
+ Camera1[CCTV Camera 1]
+ Camera2[CCTV Camera 2]
+ CameraN[CCTV Camera N]
+ Daemon[Background Daemon
Linux Service]
+ Combiner[Stream Combiner]
+ end
+
+ subgraph Cloudflare["Cloudflare Edge"]
+ SFU[Realtime SFU
WebRTC Endpoint]
+ Adapter[WebRTC to WebSocket
Adapter]
+ end
+
+ subgraph Google["Google AI"]
+ Gemini[Gemini Live API
Real-time Analysis]
+ end
+
+ subgraph Processing["CROW Processing"]
+ Queue[Interaction Queue]
+ Interaction[Interaction Service]
+ end
+
+ Camera1 --> Combiner
+ Camera2 --> Combiner
+ CameraN --> Combiner
+ Combiner --> Daemon
+ Daemon --> SFU
+ SFU --> Adapter
+ Adapter --> Gemini
+ Gemini --> Queue
+ Queue --> Interaction
+```
+
+## Key Components
+
+### Background Daemon
+
+A Linux service that runs on the CCTV server or a dedicated streaming device.
+
+**Responsibilities:**
+- Capture video streams from multiple CCTV cameras
+- Combine streams into single high-resolution view (optional)
+- Stream via WebRTC to Cloudflare Realtime SFU
+- Manage connection reliability and reconnection
+- Start automatically on system boot
+- Handle hourly session boundaries
+
+**Technology:**
+- Bash script for setup and installation
+- Background daemon process
+- Systemd service configuration
+- WebRTC client implementation
+
+**Installation:**
+```bash
+# Provided during signup component configuration
+curl -sSL https://setup.crow.example.com/cctv | bash -s YOUR_API_KEY
+```
+
+### Stream Combination
+
+Multiple CCTV camera streams can be combined into a single high-resolution view:
+
+**Benefits:**
+- AI can see all perspectives simultaneously
+- Better context for customer movement tracking
+- Reduced API calls to Gemini Live
+- More comprehensive spatial understanding
+- Easier pattern recognition across store areas
+
+**Implementation:**
+- Real-time video composition
+- Configurable layout (grid, picture-in-picture, etc.)
+- Quality optimization for bandwidth
+
+### Cloudflare Realtime SFU
+
+Cloudflare's serverless Selective Forwarding Unit for WebRTC.
+
+**Why Cloudflare Realtime SFU:**
+- Low-latency WebRTC streaming
+- Serverless architecture (no infrastructure management)
+- Global edge network for reliability
+- Native Cloudflare integration
+- Built-in scalability
+
+**Configuration:**
+- WebRTC peer connection setup
+- ICE candidate handling
+- STUN/TURN servers managed by Cloudflare
+- Automatic reconnection on failure
+
+### WebRTC to WebSocket Adapter
+
+Cloudflare provides adapters to convert WebRTC streams to WebSocket connections.
+
+**Purpose:**
+- Gemini Live API requires WebSocket input
+- Adapter bridges WebRTC (from cameras) to WebSocket (for Gemini)
+- Maintains real-time streaming characteristics
+- Handles protocol conversion efficiently
+
+### Gemini Live API
+
+Google's real-time multimodal AI API for video analysis.
+
+**Capabilities:**
+- Real-time video understanding
+- Customer movement tracking
+- Product interaction detection
+- Behavior analysis
+- Contextual scene understanding
+
+**Integration:**
+- WebSocket connection for streaming video
+- Real-time response stream
+- Contextual prompts for retail analysis
+- Organization and product context injection
+
+## Session Management
+
+### Session Definition
+
+**CCTV Session**: **1 hour of continuous footage** = one session.
+
+After each hour, the current session is closed and sent to the Interaction Service for processing, and a new session begins.
+
+### Hourly Session Creation
+
+1. **Continuous Streaming**: Daemon streams video continuously
+2. **Hourly Boundary**: Every hour, session marker is created
+3. **Gemini Processing**: Accumulated hour of analysis sent to queue
+4. **New Session Start**: Fresh session begins for next hour
+5. **Queue Dispatch**: Session data sent to Interaction Queue
+
+### Why Hourly Sessions?
+
+- **Manageable Data Size**: 1 hour of video analysis is processable
+- **Pattern Detection**: Sufficient time window for behavior patterns
+- **Resource Management**: Prevents overwhelming processing pipeline
+- **Billing Alignment**: Clear billing boundaries for usage tracking
+
+## Data Flow
+
+### Real-time Streaming Flow
+
+```mermaid
+sequenceDiagram
+ participant Camera as CCTV Cameras
+ participant Daemon as Background Daemon
+ participant SFU as Cloudflare Realtime SFU
+ participant Adapter as WebRTC→WebSocket
+ participant Gemini as Gemini Live
+ participant Queue as Interaction Queue
+
+ Camera->>Daemon: Video Streams
+ Daemon->>Daemon: Combine Streams
+
+ loop Every Frame
+ Daemon->>SFU: WebRTC Stream
+ SFU->>Adapter: Forward Stream
+ Adapter->>Gemini: WebSocket Stream
+ Gemini->>Gemini: Real-time Analysis
+ end
+
+ Note over Gemini: After 1 Hour
+
+ Gemini->>Queue: Session Analysis
+ Queue->>Interaction Service: Process Session
+```
+
+### Processing Flow
+
+1. **Video Capture**: Cameras record retail space
+2. **Stream to Cloud**: Daemon streams to Cloudflare
+3. **Real-time Analysis**: Gemini Live analyzes frames
+4. **Accumulate Insights**: Analysis accumulated over 1 hour
+5. **Session Creation**: After hour, insights compiled
+6. **Queue Dispatch**: Session sent to Interaction Queue
+7. **Interaction Processing**: Standard interaction pipeline
+8. **Pattern Recognition**: Patterns identified across sessions
+
+### Storage Strategy
+
+- **Real-time Only**: Raw video is not stored; only insights are retained
+- **Audit Frames**: For debugging or replay, selective frames/clips can be stored in R2
+- **Background Processing**: Queues handle frame storage without impacting live analysis
+- **Interaction Records**: Final insights stored in D1 with embeddings in Vectorize
+
+## Configuration Setup
+
+During signup, users configuring the CCTV component receive:
+
+### 1. Bash Script Command
+
+```bash
+# Auto-generated with API key embedded
+curl -sSL https://setup.crow.example.com/cctv | bash -s ORG_API_KEY_HERE
+```
+
+The script:
+- Installs daemon dependencies
+- Configures systemd service
+- Sets up WebRTC connection to Cloudflare
+- Embeds API key for authentication
+- Configures hourly session boundaries
+- Enables auto-start on boot
+
+### 2. API Key Generation
+
+A unique API key is generated specifically for CCTV access:
+- Scoped to organization
+- Limited to CCTV data submission
+- Used by daemon for authentication
+- Revokable from dashboard
+
+### 3. Setup Instructions
+
+- Where to run the script (CCTV server or dedicated device)
+- Network requirements and firewall rules
+- Camera configuration and selection
+- Privacy compliance guidance
+- Testing and validation steps
+
+## Privacy and Compliance
+
+### Privacy Considerations
+
+- **Selective Camera Streaming**: Not all cameras need to be streamed
+- **Privacy Zones**: Areas can be masked or excluded
+- **Data Retention**: 24-hour retention policy for compliance
+- **No PII Storage**: Focus on behavior patterns, not identification
+- **Opt-in Design**: Cameras explicitly configured
+
+### Compliance Features
+
+- **GDPR Compliance**: Data minimization and purpose limitation
+- **Retail Privacy Laws**: Adherence to retail surveillance regulations
+- **Customer Notice**: Store signage requirements
+- **Data Access Controls**: Strict access permissions
+- **Audit Logging**: All access logged
+
+### Security
+
+- **Encrypted Streaming**: TLS 1.3 for all video transmission
+- **API Key Authentication**: Daemon authenticated to upload
+- **Edge Processing**: Analysis at edge, not centralized
+- **Access Controls**: Role-based dashboard access
+
+## Analytics and Insights
+
+### Generated Insights
+
+The CCTV component generates rich insights about:
+
+**Customer Behavior:**
+- Store navigation patterns
+- Product viewing time
+- Dwell time at displays
+- Group vs. individual shopping
+- Return visits to products
+
+**Product Interactions:**
+- Products picked up
+- Products returned to shelf
+- Comparison shopping behavior
+- Product location effectiveness
+
+**Store Operations:**
+- High-traffic areas
+- Bottleneck identification
+- Staff interaction patterns
+- Queue lengths and wait times
+
+**Patterns Over Time:**
+- Peak hours and days
+- Seasonal behavior changes
+- Campaign effectiveness
+- Store layout optimization opportunities
+
+### Integration with Other Components
+
+CCTV insights are combined with Web and Social data:
+- Correlate in-store behavior with online research
+- Match physical purchases with web browsing
+- Identify social media influence on in-store visits
+- Complete customer journey mapping
+
+## Performance Characteristics
+
+### Latency
+
+- **Streaming Latency**: < 2 seconds camera to Gemini
+- **Analysis Latency**: Near real-time (< 5 seconds)
+- **Session Processing**: < 10 minutes after hourly boundary
+
+### Bandwidth
+
+- **Per Camera**: 2-5 Mbps depending on quality
+- **Combined Stream**: Optimized for bandwidth efficiency
+- **Upload Requirements**: Stable broadband connection
+
+### Scalability
+
+- **Cameras per Store**: 1-20+ cameras supported
+- **Multiple Stores**: Each store has independent daemon
+- **Concurrent Processing**: Cloudflare handles scaling
+
+## Troubleshooting
+
+### Common Issues
+
+**Connection Failures:**
+- Verify network connectivity
+- Check firewall rules for WebRTC
+- Validate API key
+- Review daemon logs
+
+**Stream Quality:**
+- Check camera resolution settings
+- Verify bandwidth availability
+- Adjust quality settings
+- Monitor network stability
+
+**Processing Delays:**
+- Check Interaction Queue health
+- Verify Gemini Live API status
+- Review resource usage
+- Contact support if persistent
+
+## Future Enhancements
+
+### Planned Features
+
+- **Multi-store Aggregation**: Patterns across store locations
+- **Real-time Alerts**: Immediate notifications for events
+- **Advanced Analytics**: Heatmaps and journey visualization
+- **Integration APIs**: Third-party analytics tool integration
+- **ML Model Training**: Custom models for specific retail needs
+
+## Related Documentation
+
+- [System Architecture](../architecture/system-architecture.md) - Overall CCTV component architecture
+- [User Signup Flow](./user-signup-flow.md) - CCTV configuration during signup
+- [Dashboard Features](./dashboard-features.md) - CCTV settings and management
+- [Website Interaction Tracking](./website-interaction-tracking.md) - Web component for comparison
diff --git a/docs/features/chat-system.md b/docs/features/chat-system.md
new file mode 100644
index 0000000..b77e350
--- /dev/null
+++ b/docs/features/chat-system.md
@@ -0,0 +1,257 @@
+---
+sidebar_position: 3
+---
+
+# Chat System
+
+## Overview
+
+The CROW dashboard features a comprehensive **chat application** powered by a multi-agentic AI system. Users can interact with their data through natural language queries, getting insights, generating reports, and exploring patterns across all data sources.
+
+## Multi-Agentic Architecture
+
+The chat system employs a **multi-agentic setup** where multiple AI agents work concurrently to provide comprehensive answers.
+
+### How It Works
+
+1. **Query Understanding**: User's natural language query is analyzed
+2. **Agent Dispatch**: Multiple agents are dispatched concurrently:
+ - Interaction Agent: Queries Interaction Service and raw interaction data
+ - Pattern Agent: Queries Pattern Service for trend analysis
+ - Product Agent: Retrieves product context and associations
+ - Analytics Agent: Computes metrics and aggregations
+3. **Concurrent Execution**: Agents work in parallel across different data sources
+4. **Result Aggregation**: Responses from all agents are combined
+5. **Response Generation**: Unified answer generated using Gemini AI
+6. **Streaming Response**: Answer streamed back to user in real-time
+
+### Agent Framework
+
+- **Vercel AI SDK**: Used for orchestrating multi-agent system
+- **Gemini Models**: All agents use Google Gemini for AI processing
+- **Cloudflare AI Gateway**: Routes all LLM requests for monitoring and optimization
+
+## Chat Service (Dashboard)
+
+The Chat Service is a **BFF (Backend for Frontend)** service specifically designed for the dashboard's chat application.
+
+**Purpose**: Provide chat-specific functionality without being a generic reusable service.
+
+### Responsibilities
+
+- **Chat History Management**: Store and retrieve past conversations
+- **Message Storage**: Persist all chat messages
+- **Artifacts Management**: Handle generated files, reports, and visualizations
+- **Assets Storage**: Manage images, charts, and other chat-related assets
+- **Session Context**: Maintain conversation context across messages
+- **Multi-Agentic Orchestration**: Coordinate agent dispatching and response aggregation
+
+### Technology Stack
+
+- TypeScript service on Cloudflare Workers
+- Gemini AI models via Vercel AI SDK
+- Cloudflare AI Gateway for LLM request routing
+- D1 database for chat history
+- R2 storage for artifacts and assets
+- Vectorize for semantic search across past conversations
+
+### Capabilities
+
+- **Natural Language Queries**: Ask questions in plain English
+- **Context-Aware Responses**: Understands organizational and product context
+- **Multi-turn Conversations**: Remembers conversation history within session
+- **Export Generation**: Create reports in various formats
+- **Visualization Creation**: Generate charts and diagrams
+- **Depth Control**: Configure analysis depth (quick vs. deep analysis)
+- **Duration Filtering**: Query specific time ranges (with user permission constraints)
+- **Component Filtering**: Focus on specific data sources (Web, Social, CCTV)
+- **Product Filtering**: Analyze specific products or product groups
+- **Concurrent Processing**: Multiple agents work simultaneously for faster responses
+
+### User Permissions Integration
+
+Chat access is controlled by user permissions:
+
+- **Duration Constraints**: Minimum duration (e.g., 1 year) set by admin
+- **Component Constraints**: Minimum 1 component, up to all 3 (Web, Social, CCTV)
+- **Query Validation**: System enforces constraints before processing queries
+
+**[→ Learn more about User Permission Levels](../reference/user-permissions.md)**
+
+## Architecture
+
+```mermaid
+flowchart LR
+ A[User Query] --> B[Chat Service]
+ B --> C[Multi-Agent Coordinator]
+ C --> D[Interaction Agent]
+ C --> E[Pattern Agent]
+ C --> F[Product Agent]
+ C --> G[Analytics Agent]
+ D --> H[Interaction Service]
+ E --> I[Pattern Service]
+ F --> J[Product Service]
+ G --> K[Vectorize Search]
+ H --> L[Gemini AI]
+ I --> L
+ J --> L
+ K --> L
+ L --> M[Response Aggregation]
+ M --> N[Streaming Response]
+ N --> O[User]
+```
+
+### Data Sources
+
+The multi-agentic system queries across multiple services:
+
+- **Interaction Service**: Raw interaction data via MCP-like interface
+- **Pattern Service**: Discovered patterns across time periods
+- **Product Service**: Product catalog and context
+- **Organization Service**: Organization context from Vectorize
+- **Vectorize**: Semantic search across all data
+- **D1 Database**: Metadata and structured queries
+- **R2 Storage**: Historical data and archives
+
+## Query Examples
+
+Users can ask questions like:
+
+### Data Queries
+
+- "How many users viewed Product X last week?"
+- "What's the conversion rate for our landing page?"
+- "Show me the top 10 most viewed products"
+
+### Reports
+
+- "Generate a weekly summary of user engagement"
+- "Create a report on cart abandonment rates"
+- "Analyze user behavior patterns for Product Y"
+
+### Analytics
+
+- "Which products have the highest interaction rates?"
+- "What's the average time users spend on product pages?"
+- "Show me products with declining interest"
+
+### Patterns
+
+- "What paths do users take before purchasing?"
+- "Identify common drop-off points"
+- "Show me user segments based on behavior"
+
+## Processing Flow
+
+### Query Processing
+
+1. **Query Received**: User submits natural language query
+2. **Intent Classification**: Determine query type
+3. **Context Retrieval**: Fetch relevant context from Vectorize
+4. **Data Fetching**: Query D1 for specific data
+5. **Response Generation**: Generate response using LLM
+6. **Formatting**: Format response for display
+
+### Semantic Search
+
+The ai-chat-service uses Vectorize for semantic search:
+
+```mermaid
+flowchart TD
+ A[User Query] --> B[Embed Query]
+ B --> C[Vectorize Search]
+ C --> D[Top-K Results]
+ D --> E[Fetch Metadata from D1]
+ E --> F[Build Context]
+ F --> G[LLM Generation]
+ G --> H[Response]
+```
+
+## Export Capabilities
+
+The chat system supports multiple export formats:
+
+### Diagrams
+
+- **Mermaid**: Flowcharts, sequence diagrams
+- **Charts**: Bar, line, pie charts
+- **Tables**: Formatted data tables
+
+### Documents
+
+- **PDF**: Professional reports
+- **LaTeX**: Academic format
+- **Markdown**: Documentation
+
+### Data
+
+- **CSV**: Spreadsheet-compatible
+- **JSON**: Programmatic access
+- **Excel**: Rich formatting
+
+## Conversation Features
+
+### Multi-turn Context
+
+The chat maintains conversation context:
+
+```
+User: "Show me sales for Product X"
+Bot: [Shows sales data]
+
+User: "How does that compare to last month?"
+Bot: [Shows comparison, understanding context]
+```
+
+### Query Refinement
+
+Users can refine queries:
+
+```
+User: "Show me user interactions"
+Bot: "I found 125,432 interactions. Filter by date, product, or source?"
+
+User: "Filter by last month"
+Bot: [Shows filtered results]
+```
+
+## Integration
+
+### Vectorize Integration
+
+- Query embeddings for semantic search
+- Interaction context retrieval
+- Product similarity matching
+
+### D1 Integration
+
+- User and organization context
+- Product catalog queries
+- Interaction metadata
+
+### R2 Integration
+
+- Export file storage
+- Generated report access
+
+## Performance
+
+### Response Times
+
+| Query Type | Target Time |
+|-----------|------------|
+| Simple queries | < 2 seconds |
+| Complex analytics | < 10 seconds |
+| Report generation | < 30 seconds |
+
+### Optimizations
+
+- Query result caching
+- Pre-computed aggregations
+- Streaming responses for long queries
+
+## Related Documentation
+
+- [System Architecture](../architecture/system-architecture.md) - Overall architecture
+- [Integration API](../architecture/integration-api.md) - API details
+- [Data Storage](../architecture/data-lake-architecture.md) - Storage design
diff --git a/docs/features/dashboard-features.md b/docs/features/dashboard-features.md
new file mode 100644
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+---
+sidebar_position: 5
+---
+
+# Dashboard Features
+
+## Overview
+
+The CROW Dashboard provides a comprehensive interface for managing organizations, analyzing data, and interacting with the platform. The dashboard is designed to serve multiple roles within an organization, from executives viewing high-level analytics to developers managing integrations.
+
+## Dashboard Pages
+
+### Overview
+
+The Overview page is a unified view combining key metrics and insights from all other dashboard sections.
+
+**Features:**
+- Organization-level analytics summary
+- Recent chat conversations
+- Latest interactions and patterns highlights
+- Quick links to common tasks
+- Component status indicators (Web, Social, CCTV)
+- Usage and billing snapshot
+
+**Purpose:** Provides a single pane of glass for quick platform status assessment without navigating through multiple pages.
+
+### Chat
+
+A conversational AI interface powered by a multi-agentic system for querying and analyzing interaction data.
+
+**Features:**
+- **Natural Language Queries**: Ask questions in plain English
+- **Multi-Agentic System**: Multiple AI agents work concurrently across data sources
+- **Context-Aware Responses**: Understands organization and product context
+- **Historical Conversations**: Access previous chat sessions
+- **Depth Levels**: Control analysis depth (quick overview vs. deep analysis)
+- **Duration Filters**: Query specific time ranges
+- **Component Filtering**: Filter by data source (Web, Social, CCTV)
+- **Product Filtering**: Focus on specific products
+- **Export Capabilities**: Export chat results as reports
+
+**Multi-Agentic Setup:**
+- Agents query across Interaction Service, Pattern Service, and data storage
+- Concurrent processing for faster responses
+- Intelligent routing based on query type
+- Consolidated results from multiple agents
+
+**Permission-Based Access:**
+- Duration constraints (e.g., minimum 1 year of data)
+- Component constraints (e.g., only Web and Social)
+- Configured per user by admins
+
+**[→ Learn more about Chat System](../features/chat-system.md)**
+
+### Insights
+
+#### Interactions Tab
+Displays raw interaction records from all data sources.
+
+**Features:**
+- View individual interaction records
+- Filter by date range
+- Filter by component source (Web, Social, CCTV)
+- Filter by product
+- Search functionality
+- Detailed interaction view with metadata
+- Product associations
+- Export interactions as CSV/JSON
+
+**Use Cases:**
+- Debugging integration issues
+- Auditing specific user sessions
+- Analyzing individual customer journeys
+- Quality assurance of data collection
+
+#### Patterns Tab
+Displays discovered patterns across interactions.
+
+**Features:**
+- View pattern records
+- Time-based aggregation levels (day, week, month, year, all-time)
+- Filter by date range
+- Filter by component source
+- Filter by product
+- Pattern confidence scores
+- Trend visualization
+- Export patterns as CSV/JSON
+
+**Use Cases:**
+- Identifying customer behavior trends
+- Strategic planning with long-term patterns
+- Product optimization based on usage patterns
+- Marketing insights from social patterns
+
+### Team
+
+Manage organization team members and their permissions.
+
+**Features:**
+- **Invite Members**: Send email invitations to new team members
+- **View Members**: List all organization members
+- **Edit Permissions**: Modify user permission levels
+- **Remove Members**: Remove users from organization
+- **Permission Templates**: Quick apply common permission sets
+- **Invitation Status**: Track pending invitations
+
+**Permission Management:**
+- Toggle feature access on/off
+- Set chat duration constraints
+- Configure component access
+- Assign permission levels
+
+**Validation:**
+- Check if invitee already has an organization (1:1 constraint)
+- Verify email validity
+- Prevent duplicate invitations
+
+**[→ Learn more about User Permission Levels](../reference/user-permissions.md)**
+
+### Notifications
+
+View and manage all user notifications.
+
+**Features:**
+- Notification history (all past notifications)
+- Unread notification count
+- Mark as read/unread
+- Filter by type (system, alerts, updates, invitations)
+- Clear notification history
+- Notification preferences (future)
+
+**Notification Types:**
+- System updates and maintenance
+- Usage alerts (approaching limits)
+- Processing completion notifications
+- Team invitation notifications
+- Integration status changes
+- Error alerts
+
+### Billing / Analytics
+
+View usage metrics, costs, and manage billing.
+
+**Features:**
+- **Current Usage**: Real-time interaction and pattern counts
+- **Cost Breakdown**: Current month's charges
+- **Billing Plans**: View selected components and pricing
+- **Usage Trends**: Historical usage charts
+- **Cost Projections**: Estimated end-of-month cost
+- **Invoice History**: Download past invoices
+- **Payment Methods**: Update payment information
+- **Usage Alerts**: Configure alert thresholds
+
+**Pricing Display:**
+- Base price per component
+- Included volume (1 million interactions/patterns)
+- Additional volume charges
+- Total estimated cost
+- Per-component breakdown
+
+**Analytics:**
+- Interactions over time
+- Patterns discovered over time
+- Component-specific usage
+- Product-level analytics
+
+### Settings
+
+A collection of configuration and management features.
+
+#### API Keys
+
+Manage API keys for external integrations.
+
+**Features:**
+- Create new API keys
+- List all keys with metadata
+- Revoke keys
+- Set key expiration
+- Configure key permissions (interactions, patterns)
+- View key usage statistics
+- Regenerate keys
+
+**Security:**
+- Keys are encrypted at rest
+- One-time display on creation
+- Automatic expiration support
+- Instant revocation
+
+**[→ Learn more about Integration API](../architecture/integration-api.md)**
+
+#### Integrations
+
+Configure Web, Social, and CCTV components.
+
+**Features:**
+- **Web Integration**: SDK installation and code snippets
+- **Social Integration**: Social media account links
+- **CCTV Integration**: Bash script and streaming configuration
+- View integration status
+- Test connections
+- Update configurations
+- View component-specific metrics
+
+**Component Status:**
+- Active/Inactive indicator
+- Last data received timestamp
+- Error states and troubleshooting
+- Data flow validation
+
+#### Profile
+
+Manage user profile information.
+
+**Features:**
+- Update username
+- Update email address
+- Change password
+- Password reset
+- Two-factor authentication (future)
+- Profile picture upload
+- Notification preferences
+- Language and timezone settings
+
+#### Product Management
+
+Comprehensive product catalog management.
+
+**Features:**
+- **View Products**: List all products with details
+- **Search & Filter**: Find products quickly
+- **Edit Products**: Update product information
+- **Bulk Operations**: Update multiple products
+- **Refinement**: Edit AI-extracted product data
+- **Product Details**: Name, description, URL, price, images
+- **Product Associations**: View interactions and patterns per product
+- **Import/Export**: CSV import/export for bulk updates
+
+**Data Sources:**
+- Initial CSV upload during signup
+- Web scraping during signup
+- Manual additions and edits
+- Future: Re-scraping capabilities (planned)
+
+**Refinement Workflow:**
+1. View scraped products
+2. Select products to refine
+3. Edit fields as needed
+4. Apply changes
+5. Changes reflected in future analytics
+
+**Limitations (Current):**
+- Cannot re-scrape entire website
+- Cannot scrape separate URLs after initial setup
+- Can refine existing data only
+- All versions maintained for audit
+
+**Future Enhancements:**
+- Re-scrape functionality
+- Product versioning and history
+- Automated product updates
+- Product relationship mapping
+
+**[→ Learn more about Product Scraping](../features/product-scraping.md)**
+
+#### Web Hooks (Optional)
+
+**Status**: Marked as optional, not part of core architecture.
+
+Future feature for integrating CROW with external systems via webhooks.
+
+**Planned Features:**
+- Configure webhook endpoints
+- Select events to trigger webhooks
+- Secure webhook signing
+- Retry logic for failed webhooks
+- Webhook event log
+- Testing interface
+
+## Dashboard Architecture
+
+### Client Technology
+- React SPA deployed on Cloudflare Workers
+- Real-time updates via WebSockets
+- Optimized for interactivity
+- Code splitting for performance
+
+### Data Flow
+1. User interacts with dashboard
+2. Request sent to API Gateway
+3. Session validated via Auth Service
+4. Request routed to appropriate service
+5. Data fetched and returned
+6. Dashboard updates UI
+
+### Real-time Features
+- Live usage metrics
+- Chat streaming responses
+- Notification updates
+- Integration status changes
+
+### State Management
+- Client-side state for UI
+- Server-side session state
+- Optimistic updates for better UX
+- Background sync for data consistency
+
+## User Experience
+
+### Navigation
+- Persistent sidebar with main menu
+- Breadcrumb navigation for deep pages
+- Quick search for all features
+- Keyboard shortcuts for power users
+
+### Responsive Design
+- Fully responsive for desktop, tablet, mobile
+- Adaptive layouts based on screen size
+- Touch-optimized for mobile devices
+
+### Accessibility
+- WCAG 2.1 AA compliance
+- Keyboard navigation support
+- Screen reader compatibility
+- High contrast mode
+
+### Performance
+- Sub-2-second page load times
+- Optimistic UI updates
+- Background data fetching
+- Progressive enhancement
+
+## Related Documentation
+
+- [Frontend Architecture](../architecture/frontend-architecture.md) - Dashboard technical architecture
+- [User Signup Flow](../features/user-signup-flow.md) - How users reach the dashboard
+- [Chat System](../features/chat-system.md) - Chat functionality details
+- [User Permission Levels](../reference/user-permissions.md) - Access control for dashboard features
diff --git a/docs/features/product-scraping.md b/docs/features/product-scraping.md
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+---
+sidebar_position: 2
+---
+
+# Product Scraping
+
+## Overview
+
+CROW's product onboarding system allows organizations to quickly populate their product catalog through multiple methods. The **ai-scraping-service** provides intelligent web scraping powered by AI to automatically extract product information from company websites.
+
+## Product Onboarding Flow
+
+When users create their organization, they can add products through two methods:
+
+### 1. CSV Import
+
+**Direct bulk upload of product data**
+
+- Upload a CSV file with product information
+- Supports standard product fields (name, description, SKU, price, etc.)
+- Immediate import with validation
+- Files stored in R2, metadata in D1
+
+**Use Cases**:
+- Migrating from existing systems
+- Bulk product catalog updates
+- Standardized product data
+
+### 2. Web Scraping
+
+**Automated extraction via Product Service**
+
+- Provide company website URL
+- AI automatically discovers and extracts product information
+- Background processing via Cloudflare Queues
+- Uses Cloudflare Browser Rendering for dynamic content
+- Analyzes sitemap.xml for context
+- Refinement interface for quality assurance
+
+**Use Cases**:
+- New organization setup
+- Automated product discovery
+- Initial product catalog population
+
+### Technology
+
+- Cloudflare Browser Rendering for JavaScript-rendered pages
+- Gemini AI via Vercel AI SDK for product extraction
+- Tavily for AI-optimized web search and lightweight content extraction
+- Sitemap.xml analysis for site structure understanding
+- Queue-based processing for scalability
+
+## Product Service
+
+The Product Service handles all product-related operations including catalog management and web scraping.
+
+### Capabilities
+
+- **Product CRUD**: Create, read, update, delete products
+- **Multi-page Crawling**: Navigate complex website structures
+- **Dynamic Content**: Handle JavaScript-rendered pages via Browser Rendering
+- **Product Extraction**: Identify and extract product information using Gemini AI
+- **Sitemap Analysis**: Use sitemap.xml for context and site structure
+- **Data Normalization**: Standardize extracted data
+- **Vectorize Integration**: Maintain product embeddings for search
+
+### Technology Stack
+
+- TypeScript on Cloudflare Workers
+- Cloudflare Browser Rendering for web scraping
+- Gemini AI via Vercel AI SDK for extraction
+- Cloudflare AI Gateway for LLM request routing
+- Vectorize for product embeddings
+
+### Architecture
+
+```mermaid
+flowchart TD
+ A[Scrape Request
During Signup] --> B[Cloudflare Queue]
+ B --> C[Product Service]
+ C --> D[URL Validation]
+ D --> E[Sitemap.xml Analysis]
+ E --> F[Browser Rendering
Page Fetch]
+ F --> G[Gemini AI
Product Extraction]
+ G --> H[Data Normalization]
+ H --> I[Store in D1]
+ I --> J[Generate Embeddings]
+ J --> K[Store in Vectorize]
+ K --> L[Refinement UI
User Review]
+```
+
+### Workflow Steps
+
+1. **URL Validation**: Verify target website accessibility
+2. **Sitemap Analysis**: Parse sitemap.xml for site structure and context
+3. **Page Crawling**: Navigate and extract content using Browser Rendering
+4. **AI Extraction**: Use Gemini models to identify and extract products
+5. **Data Normalization**: Standardize product format
+6. **Storage**: Save to D1 and generate embeddings
+7. **Vectorize**: Store embeddings for semantic search
+8. **User Refinement**: Allow user to review and edit extracted data
+
+## Multi-Agent Extraction Pipeline
+
+The Product Service uses a multi-agent orchestration system for intelligent product extraction. Each agent has a specialized role in the extraction workflow.
+
+### Agent Architecture
+
+```mermaid
+flowchart LR
+ subgraph Orchestration["Agent Orchestration"]
+ Planner[Planner Agent]
+ Discoverer[Discoverer Agent]
+ Extractor[Extractor Agent]
+ Validator[Validator Agent]
+ Refiner[Refiner Agent]
+ end
+
+ Planner --> Discoverer
+ Discoverer --> Extractor
+ Extractor --> Validator
+ Validator --> Refiner
+ Refiner --> Storage[(D1 + Vectorize)]
+```
+
+### Agent Roles
+
+| Agent | Role | Capability |
+|-------|------|------------|
+| **Planner** | Strategy definition | Analyzes target source and plans extraction steps |
+| **Discoverer** | Content discovery | Finds relevant pages using web search from known links |
+| **Extractor** | Data extraction | Uses Browser Rendering to extract structured fields |
+| **Validator** | Quality assurance | Normalizes fields into expected schema, validates required attributes |
+| **Refiner** | Enhancement | Improves records with extra context (cleaner descriptions, tags) |
+
+### Reusable Design
+
+The agent structure supports reprocessing without full re-extraction:
+
+- Raw extraction artifacts stored in R2
+- Organizations can refine products using stored artifacts
+- Reduces redundant network requests
+- Enables quality improvements over time
+
+## Scraping Process
+
+### Job Lifecycle
+
+```mermaid
+stateDiagram-v2
+ [*] --> Queued
+ Queued --> Processing
+ Processing --> Extracting
+ Extracting --> Normalizing
+ Normalizing --> Complete
+ Processing --> Failed
+ Extracting --> Failed
+ Failed --> [*]
+ Complete --> [*]
+```
+
+### Rate Limiting
+
+The ai-scraping-service implements responsible scraping:
+
+- Respects robots.txt
+- Configurable request delays
+- Domain-based rate limits
+- Automatic backoff on errors
+
+## Product Refinement
+
+After scraping completes, users can review and refine results in the Dashboard > Settings > Product Management:
+
+### Refinement Interface
+
+- **View Extracted Products**: See all products with extraction confidence scores
+- **Edit Fields**: Modify name, description, price, images
+- **Select and Refine**: Choose specific products or rows to edit
+- **Bulk Operations**: Edit multiple products at once
+- **Apply Changes**: Changes reflected in future analytics
+
+### Quality Metrics
+
+- Extraction confidence scores (AI certainty)
+- Field completeness percentage
+- Duplicate detection flags
+- Validation errors highlighted
+
+### Current Limitations
+
+**What You Can Do:**
+- Upload CSV during initial setup
+- Provide URL for scraping during setup
+- Refine existing product data (edit fields, update information)
+- Manual additions and edits anytime
+
+**What You Cannot Do (Currently):**
+- Re-scrape entire website after initial setup
+- Scrape a different URL after initial setup
+- Automated re-scraping on schedule
+
+**Rationale**: Product version management is complex. To maintain data integrity and audit trails, the system currently restricts re-scraping. All product versions would need to be maintained, which is planned for future releases.
+
+### Future Enhancements
+
+Planned features for product management:
+- **Re-scrape Functionality**: Re-scrape entire website with version tracking
+- **Separate URL Scraping**: Scrape additional URLs after setup
+- **Version History**: View and compare product data across versions
+- **Automated Updates**: Schedule regular product updates
+- **Change Detection**: Alert on product changes
+- **Product Relationships**: Map related products and categories
+
+## Storage
+
+### D1 Schema
+
+```sql
+CREATE TABLE products (
+ id TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL REFERENCES organizations(id),
+ name TEXT NOT NULL,
+ description TEXT,
+ url TEXT,
+ price REAL,
+ currency TEXT,
+ image_url TEXT,
+ metadata JSON,
+ source TEXT,
+ confidence REAL,
+ created_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+
+CREATE TABLE scrape_jobs (
+ id TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL REFERENCES organizations(id),
+ url TEXT NOT NULL,
+ status TEXT DEFAULT 'queued',
+ products_found INTEGER DEFAULT 0,
+ error TEXT,
+ started_at DATETIME,
+ completed_at DATETIME
+);
+```
+
+### Vectorize Index
+
+Product embeddings stored for semantic search:
+
+- Index: `product-embeddings`
+- Dimensions: 1536 (OpenAI ada-002)
+- Metadata: org_id, category, source
+
+## Error Handling
+
+### Common Errors
+
+| Error | Cause | Resolution |
+|-------|-------|------------|
+| Site Unreachable | Network/DNS issues | Retry with backoff |
+| Blocked | Anti-bot measures | Manual review |
+| Parse Error | Unusual HTML structure | AI fallback |
+| Rate Limited | Too many requests | Increase delays |
+
+### Recovery
+
+- Partial results saved on failure
+- Jobs can be resumed
+- Manual scraping option for problematic sites
+
+## Related Documentation
+
+- [User Signup Flow](./user-signup-flow.md) - Product onboarding in signup
+- [System Architecture](../architecture/system-architecture.md) - Overall architecture
+- [Data Storage](../architecture/data-lake-architecture.md) - Where products are stored
diff --git a/docs/features/social-media-component.md b/docs/features/social-media-component.md
new file mode 100644
index 0000000..6c86a26
--- /dev/null
+++ b/docs/features/social-media-component.md
@@ -0,0 +1,500 @@
+---
+sidebar_position: 7
+---
+
+# Social Media Component
+
+## Overview
+
+The Social Media component is CROW's **Phase 2** offering, deployed after the Web component but before CCTV. It performs intelligent web searching and extraction of social media data, analyzing company social media posts, comments, and engagement to track public sentiment and brand perception.
+
+## Why Social is Phase 2
+
+The Social component leverages the core infrastructure built for the Web component:
+- Uses same Interaction and Pattern services
+- Leverages established queue architecture
+- Builds on existing Organization and Product context
+- Requires less infrastructure than CCTV
+- Provides valuable insights while CCTV is developed
+
+## Architecture
+
+```mermaid
+flowchart TB
+ subgraph Triggers["Cron Triggers"]
+ CronJob[Scheduled Cron
Daily/Hourly]
+ end
+
+ subgraph Social["Social Worker"]
+ Branch{Scraping Type}
+ AISearch[AI-Generated
Web Search]
+ DirectScrape[Social Media
Link Scraping]
+ end
+
+ subgraph Search["Web Search"]
+ QueryGen[Gemini AI
Generate Queries]
+ WebSearch[Execute Searches]
+ LinkExtract[Extract Unique Links]
+ end
+
+ subgraph Scraping["Content Extraction"]
+ Browser[Cloudflare
Browser Rendering]
+ Extract[Web Extraction]
+ Dedup[Duplicate Detection]
+ end
+
+ subgraph Processing["CROW Processing"]
+ Queue[Interaction Queue]
+ Interaction[Interaction Service]
+ end
+
+ CronJob --> Branch
+ Branch -->|Path 1| AISearch
+ Branch -->|Path 2| DirectScrape
+
+ AISearch --> QueryGen
+ QueryGen --> WebSearch
+ WebSearch --> LinkExtract
+ LinkExtract --> Browser
+
+ DirectScrape --> Browser
+ Browser --> Extract
+ Extract --> Dedup
+ Dedup --> Queue
+ Queue --> Interaction
+```
+
+## Two-Part Approach
+
+The Social component operates through two distinct methods:
+
+### 1. AI-Generated Web Search
+
+**Process:**
+1. **Query Generation**: Gemini AI generates search queries about the organization
+2. **Web Search Execution**: Queries executed via search APIs
+3. **Link Extraction**: Search results parsed for unique URLs
+4. **Duplicate Detection**: Already-seen links filtered out
+5. **Web Extraction**: New links scraped via Browser Rendering
+6. **Queue Dispatch**: Extracted content sent to Interaction Queue
+
+**Query Examples:**
+- "[Company Name] customer reviews"
+- "[Product Name] social media mentions"
+- "[Brand] latest news"
+- "[Company] twitter discussions"
+
+**Technology:**
+- Gemini AI via Vercel AI SDK for query generation
+- Tavily for AI-optimized web search and content extraction
+- Cloudflare Browser Rendering for extraction
+
+#### Multi-Agent Search System
+
+The AI-generated web search uses a multi-agent orchestration system:
+
+```mermaid
+flowchart LR
+ subgraph Agents["Search Agents"]
+ Planner[Search Planner]
+ Executor[Search Executor]
+ Extractor[Content Extractor]
+ Standardizer[Standardizer]
+ Dedup[Deduplication]
+ end
+
+ Planner --> Executor
+ Executor --> Extractor
+ Extractor --> Standardizer
+ Standardizer --> Dedup
+ Dedup --> Queue[(Interaction Queue)]
+```
+
+| Agent | Role |
+|-------|------|
+| **Search Planner** | Generates and refines search queries for brand/products |
+| **Search Executor** | Runs queries via web search provider, collects candidate links |
+| **Content Extractor** | Retrieves and parses discovered content |
+| **Standardizer** | Maps fields into required schema, validates attributes |
+| **Deduplication** | Removes duplicate content across sources |
+
+The Search Planner applies advanced search techniques including Boolean operators, site-specific targeting, and time-based filtering. Using multiple search engines improves coverage and reduces the risk of missing relevant content.
+
+### 2. Social Media Link Scraping
+
+**Process:**
+1. **Configuration**: User provides social media account links during setup
+2. **Direct Scraping**: Cron job triggers scraping of provided accounts
+3. **Content Extraction**: Posts, comments, engagement data extracted
+4. **Platform APIs**: Use official APIs where available
+5. **Web Extraction**: Fallback to Browser Rendering when needed
+6. **Queue Dispatch**: Content sent to Interaction Queue
+
+**Supported Platforms:**
+- Twitter/X
+- LinkedIn
+- Facebook
+- Instagram
+- Reddit
+- TikTok
+- YouTube
+
+## Session Management
+
+### Session Definition
+
+**Social Media Session**: **One cron job trigger execution** = one session.
+
+Each scheduled cron run processes and analyzes content as a complete session, then sends it to the Interaction Service.
+
+### Cron Schedule
+
+Configurable scheduling options:
+- **Daily**: Once per day (default)
+- **Hourly**: Every hour (high-volume brands)
+- **Custom**: Specific times or intervals
+
+### Session Processing
+
+1. **Cron Triggers**: Scheduled execution starts
+2. **Both Paths Execute**: AI search AND direct scraping run
+3. **Content Aggregation**: All extracted content combined
+4. **Session Creation**: Results compiled into session
+5. **Queue Dispatch**: Complete session sent to Interaction Queue
+6. **Interaction Processing**: Standard pipeline processes session
+
+## Social Worker
+
+### Service Details
+
+**Service Name**: `social-worker`
+
+**Technology**: TypeScript on Cloudflare Workers
+
+**Deployment**: Edge-deployed, cron-triggered
+
+### Responsibilities
+
+- **Cron-based Execution**: Runs on schedule
+- **AI Query Generation**: Creates search queries using Gemini
+- **Web Search**: Executes queries and processes results
+- **Link Management**: Tracks seen/unseen links in D1
+- **Direct Scraping**: Fetches from provided social media links
+- **Web Extraction**: Uses Browser Rendering for content
+- **Duplicate Detection**: Prevents reprocessing same content
+- **Queue Dispatch**: Sends sessions to processing
+
+### Technology Stack
+
+- TypeScript on Cloudflare Workers
+- Gemini AI via Vercel AI SDK
+- Cloudflare Browser Rendering
+- Cloudflare AI Gateway for LLM routing
+- D1 for link tracking
+- Cron Triggers for scheduling
+
+## Configuration Setup
+
+During signup, users configuring the Social component provide:
+
+### 1. Social Media Links
+
+Users provide URLs to their social media accounts:
+
+```
+Twitter/X: https://twitter.com/company
+LinkedIn: https://linkedin.com/company/company-name
+Facebook: https://facebook.com/company-page
+Instagram: https://instagram.com/company
+Reddit: https://reddit.com/r/company
+```
+
+### 2. API Key Generation
+
+A unique API key is generated specifically for social data:
+- Scoped to organization
+- Used for authenticated requests
+- Managed from dashboard
+- Revokable at any time
+
+### 3. Schedule Configuration
+
+Users can configure:
+- Scraping frequency (daily, hourly, custom)
+- Specific time windows
+- Platform priorities
+- Content type preferences
+
+## Data Extraction
+
+### Extracted Data Points
+
+**For Each Social Post:**
+- Post text/caption
+- Author information
+- Post timestamp
+- Engagement metrics (likes, shares, comments)
+- Media URLs (images, videos)
+- Hashtags and mentions
+- Post URL/ID
+
+**For Comments:**
+- Comment text
+- Author information
+- Comment timestamp
+- Engagement metrics
+- Reply relationships
+- Sentiment indicators
+
+**For Engagement:**
+- Total reach/impressions
+- Engagement rate
+- Audience demographics
+- Trending topics
+- Sentiment distribution
+
+### Content Types
+
+- Text posts and updates
+- Images and videos
+- Stories and ephemeral content (where accessible)
+- Comments and replies
+- Shares and retweets
+- Reactions and likes
+- Reviews and ratings
+
+## Duplicate Detection
+
+### Link Tracking
+
+**D1 Database Schema:**
+```sql
+CREATE TABLE seen_links (
+ url TEXT PRIMARY KEY,
+ org_id TEXT NOT NULL,
+ first_seen DATETIME DEFAULT CURRENT_TIMESTAMP,
+ last_checked DATETIME,
+ content_hash TEXT,
+ source TEXT
+);
+```
+
+### Detection Strategy
+
+1. **URL Normalization**: Standardize URLs before checking
+2. **Hash Comparison**: Content hash for duplicate content detection
+3. **Timestamp Tracking**: When link was first seen
+4. **Source Tracking**: Origin of the link (search vs direct)
+5. **Efficient Queries**: Indexed lookups for fast checking
+
+### Update Detection
+
+For direct social media scraping:
+- New posts always processed
+- Updated posts (edits) re-processed
+- Deleted posts marked accordingly
+- Engagement updates tracked
+
+## Processing Flow
+
+### Complete Flow Diagram
+
+```mermaid
+sequenceDiagram
+ participant Cron as Cron Trigger
+ participant Worker as Social Worker
+ participant Gemini as Gemini AI
+ participant Search as Web Search
+ participant Browser as Browser Rendering
+ participant D1 as D1 Database
+ participant Queue as Interaction Queue
+ participant Interaction as Interaction Service
+
+ Cron->>Worker: Trigger Execution
+
+ par AI-Generated Search
+ Worker->>Gemini: Generate Queries
+ Gemini->>Worker: Return Queries
+ Worker->>Search: Execute Searches
+ Search->>Worker: Return Links
+ Worker->>D1: Check Seen Links
+ D1->>Worker: New Links
+ Worker->>Browser: Scrape New Links
+ Browser->>Worker: Extracted Content
+ and Direct Social Scraping
+ Worker->>Browser: Scrape Social Links
+ Browser->>Worker: Social Content
+ end
+
+ Worker->>Worker: Combine All Content
+ Worker->>Queue: Send Session
+ Queue->>Interaction: Process Session
+ Interaction->>Interaction: Analyze with Gemini
+```
+
+## Analytics and Insights
+
+### Generated Insights
+
+The Social component generates insights about:
+
+**Brand Sentiment:**
+- Overall sentiment trends
+- Platform-specific sentiment
+- Sentiment by product/topic
+- Sentiment change over time
+
+**Engagement Patterns:**
+- Best performing content types
+- Optimal posting times
+- Audience engagement levels
+- Viral content identification
+
+**Topic Analysis:**
+- Trending topics related to brand
+- Customer pain points
+- Feature requests
+- Competitive mentions
+
+**Audience Insights:**
+- Demographics and interests
+- Geographic distribution
+- Influence and reach
+- Community growth
+
+### Pattern Recognition
+
+Pattern Service identifies long-term trends:
+- Seasonal sentiment changes
+- Campaign effectiveness
+- Crisis detection and response
+- Brand perception evolution
+- Competitive positioning shifts
+
+## Integration with Other Components
+
+Social insights combine with Web and CCTV data to provide comprehensive customer understanding:
+
+**Web + Social (Current & Planned):**
+- Correlate social mentions with website traffic
+- Identify social-driven conversions
+- Track referral effectiveness
+- Measure social ROI
+- Pattern Service identifies cross-component patterns automatically
+
+**Social + CCTV (Future Capability):**
+- Connect online buzz to in-store traffic
+- Measure campaign impact on foot traffic
+- Identify social-to-physical customer journeys
+- Requires CCTV Phase 3 deployment
+
+**Complete View (Vision):**
+- Omnichannel customer understanding across all touchpoints
+- Full funnel attribution with multi-touch analytics
+- Cross-channel pattern recognition via Pattern Service
+- Holistic brand health monitoring with unified insights
+
+The Pattern Service automatically discovers correlations between components as data accumulates. As more components are deployed, cross-component insights become richer and more actionable.
+
+## Rate Limiting and Compliance
+
+### Responsible Scraping
+
+- **Robots.txt Compliance**: Respects robots.txt directives
+- **Rate Limiting**: Configurable delays between requests
+- **Domain Limits**: Per-domain request limits
+- **Backoff Strategy**: Automatic backoff on errors
+- **User Agent**: Proper identification as CROW scraper
+
+### API Usage
+
+For platforms with APIs:
+- **Official APIs Preferred**: Use APIs when available
+- **Rate Limits**: Respect platform rate limits
+- **Token Management**: Secure token storage
+- **Quota Monitoring**: Track API usage
+
+### Terms of Service
+
+- Compliance with platform ToS
+- Ethical scraping practices
+- Public data only
+- No personal data collection
+- Transparent usage
+
+## Performance Characteristics
+
+### Execution Time
+
+- **Single Cron Run**: 5-30 minutes depending on volume
+- **Query Generation**: < 10 seconds
+- **Per Link Scraping**: 2-5 seconds
+- **Session Processing**: < 10 minutes
+
+### Scalability
+
+- **Links per Session**: Up to 1000 links
+- **Platforms**: Unlimited platforms
+- **Organizations**: Scales with Cloudflare
+- **Concurrent Jobs**: Multiple orgs processed in parallel
+
+### Reliability
+
+- **Retry Logic**: Automatic retries on failure
+- **Error Handling**: Graceful degradation
+- **Partial Results**: Partial sessions saved
+- **Monitoring**: Execution tracking and alerts
+
+## Troubleshooting
+
+### Common Issues
+
+**No New Content:**
+- Verify social media links are correct
+- Check if accounts are public
+- Review cron schedule configuration
+- Confirm API keys are valid
+
+**Duplicate Content:**
+- Check duplicate detection is enabled
+- Review link normalization logic
+- Verify content hashing
+
+**Rate Limiting:**
+- Adjust scraping frequency
+- Increase delays between requests
+- Check platform-specific limits
+- Consider API upgrades
+
+**Extraction Failures:**
+- Verify Browser Rendering quota
+- Check website structure changes
+- Review extraction selectors
+- Test individual URLs
+
+## Future Enhancements
+
+### Planned Features
+
+- **Real-time Social Listening**: WebSocket-based live monitoring
+- **Advanced Sentiment Analysis**: Emotion detection, sarcasm recognition
+- **Influencer Identification**: Key influencers and brand advocates
+- **Competitor Analysis**: Automated competitive intelligence
+- **Crisis Detection**: Early warning system for PR issues
+- **Response Suggestions**: AI-generated response recommendations
+- **Automated Reporting**: Scheduled social media reports
+
+### Under Consideration
+
+- **Video Content Analysis**: Analyze video posts and stories
+- **Image Recognition**: Visual brand mentions
+- **Hashtag Campaigns**: Campaign tracking and analytics
+- **Social Commerce**: Purchase intent and conversion tracking
+
+## Related Documentation
+
+- [System Architecture](../architecture/system-architecture.md) - Social component architecture
+- [User Signup Flow](./user-signup-flow.md) - Social configuration during signup
+- [Dashboard Features](./dashboard-features.md) - Social settings and management
+- [Website Interaction Tracking](./website-interaction-tracking.md) - Web component for comparison
+- [CCTV Component](./cctv-component.md) - CCTV component for comparison
diff --git a/docs/features/user-signup-flow.md b/docs/features/user-signup-flow.md
new file mode 100644
index 0000000..03f3fee
--- /dev/null
+++ b/docs/features/user-signup-flow.md
@@ -0,0 +1,261 @@
+---
+sidebar_position: 4
+---
+
+# User Signup Flow
+
+This section illustrates the comprehensive system flow for first-time users signing up, from account creation through organization setup, product onboarding, payment, component configuration, to reaching the dashboard.
+
+## System Flow Diagram
+
+```mermaid
+flowchart TD
+ Start([New User Arrives]) --> Auth{Authentication Method}
+
+ Auth -->|Email/Password| Password[Username/Email/Password Signup]
+ Auth -->|OAuth| OAuth[OAuth Signup]
+
+ OAuth --> AuthSuccess[Account Created]
+ Password --> Validate{Validation}
+ Validate -->|Pass| AuthSuccess
+ Validate -->|Fail| Password
+
+ AuthSuccess --> CreateOrg[Prompt: Create Organization]
+ CreateOrg --> OrgForm[Enter Organization Details]
+ OrgForm --> OrgCreated[Organization Created]
+
+ OrgCreated --> ProductSync[Product Sync Process]
+ ProductSync --> ProductMethod{Product Input Method}
+
+ ProductMethod -->|CSV Upload| CSVUpload[Upload CSV File
Validate Format]
+ ProductMethod -->|Website URL| URLInput[Provide Website URL
Initiate Scraping]
+
+ CSVUpload --> ProductValidated[Products Validated]
+ URLInput --> ProductValidated
+
+ ProductValidated --> Payment[Payment Flow]
+ Payment --> SelectComponents[Select Components]
+ SelectComponents --> ComponentSelect{Components Selected}
+
+ ComponentSelect -->|Web| WebPrice[Web Component
Base Price + Volume]
+ ComponentSelect -->|Social| SocialPrice[Social Component
Base Price + Volume]
+ ComponentSelect -->|CCTV| CCTVPrice[CCTV Component
Base Price + Volume]
+
+ WebPrice --> PriceCalculated[Calculate Total Price]
+ SocialPrice --> PriceCalculated
+ CCTVPrice --> PriceCalculated
+
+ PriceCalculated --> PaymentProcess[Payment Processing]
+ PaymentProcess --> PaymentDone[Payment Complete]
+
+ PaymentDone --> DynamicConfig[Dynamic Component Configuration]
+ DynamicConfig --> ConfigCheck{Which Components?}
+
+ ConfigCheck -->|Web Selected| WebConfig[Web Configuration]
+ ConfigCheck -->|Social Selected| SocialConfig[Social Configuration]
+ ConfigCheck -->|CCTV Selected| CCTVConfig[CCTV Configuration]
+
+ WebConfig --> WebSteps[1. Package Install Command
2. Code Snippet
3. Generate API Key]
+ SocialConfig --> SocialSteps[1. Social Media Links
2. Generate API Key]
+ CCTVConfig --> CCTVSteps[1. Bash Script Command
2. Generate API Key]
+
+ WebSteps --> AllConfigDone{All Configs Done?}
+ SocialSteps --> AllConfigDone
+ CCTVSteps --> AllConfigDone
+
+ AllConfigDone -->|More to configure| ConfigCheck
+ AllConfigDone -->|Complete| SetupProcessing[System Setup & Processing]
+
+ SetupProcessing --> Dashboard[Dashboard Home Page]
+ Dashboard --> End([Complete])
+
+ style Start fill:#e1f5e1,stroke:#2d5016,color:#000
+ style Auth fill:#fff3cd,stroke:#856404,color:#000
+ style AuthSuccess fill:#d1e7dd,stroke:#0f5132,color:#000
+ style OrgCreated fill:#d1e7dd,stroke:#0f5132,color:#000
+ style ProductValidated fill:#d1e7dd,stroke:#0f5132,color:#000
+ style PaymentDone fill:#d1e7dd,stroke:#0f5132,color:#000
+ style Dashboard fill:#d4edda,stroke:#0f5132,color:#000
+ style End fill:#e1f5e1,stroke:#2d5016,color:#000
+```
+
+## Flow Details
+
+### 1. User Signup
+
+The system provides two signup methods for new users:
+
+- **Email/Password**: Traditional username, email, and password signup with validation
+- **OAuth**: Users can sign up using third-party OAuth providers
+
+Both methods require basic validation (account doesn't exist, valid email format, etc.) before proceeding.
+
+### 2. Organization Creation
+
+After successful signup, **all new users must create their first organization**:
+
+- **Required Step**: Organization creation is mandatory for first-time users
+- **Organization Details**: Name, industry, size, and other relevant information
+- **1:1 Mapping**: Each user belongs to exactly one organization (critical constraint)
+- **Owner Role**: User who creates the organization becomes the owner
+
+**Important**: This is for first-time users only. Invited users skip this step and join an existing organization.
+
+### 3. Product Sync Process
+
+Once the organization is created, users must provide product information through one of two methods:
+
+#### CSV Upload
+- Upload a CSV file following CROW's required pattern
+- Immediate validation of format and data
+- Products are imported directly without scraping
+- ID mapping consideration: Product IDs from CSV should match IDs used in web integration
+
+#### Website URL
+- Provide a URL to the company website containing products
+- Background scraping task initiated
+- CROW scrapes product catalog automatically
+- Sitemap.xml analyzed for context
+- Product data extracted and normalized
+
+**Product ID Concern**: The product IDs in the system must match the IDs used when integrating the SDK. If the website doesn't expose internal product IDs publicly, developers may need to manually map IDs during integration.
+
+### 4. Payment Flow
+
+Users select components and configure billing:
+
+**Pricing Model:**
+- **Base Price per Component**: Each component (Web, Social, CCTV) has a base price
+- **Included Volume**: Base price includes up to 1 million interactions and patterns
+- **Additional Volume**: Extra charges for usage beyond included volume
+- **Validation**: System enforces limits - stops saving raw data if limits exceeded
+
+**Components Available:**
+- Web Component (Phase 1 - current focus)
+- Social Component (Phase 2)
+- CCTV Component (Phase 3)
+
+Users can select minimum 1 component, maximum 3 components.
+
+### 5. Dynamic Component Configuration
+
+Based on selected components, users configure each one (min 1, max 3 configurations):
+
+#### Web Component Configuration
+1. **Package Installation Command**
+ - Multiple options provided: npm, pnpm, bun, etc.
+ - Example: `npm install @crow/tracking-sdk`
+
+2. **Code Snippet**
+ - Multiple framework options: React, Electron, React Native, etc.
+ - Copy-paste integration code
+ - Pre-filled with generated API key
+
+3. **API Key Generation**
+ - Unique API key generated for web component
+ - Displayed in code snippet
+ - Stored for later management
+
+#### Social Component Configuration
+1. **Social Media Links**
+ - User provides links to company social media accounts
+ - Platforms: Twitter/X, LinkedIn, Facebook, Instagram, etc.
+ - Used for direct scraping of social content
+
+2. **API Key Generation**
+ - Unique API key generated for social component
+ - Used for authenticated access
+
+#### CCTV Component Configuration
+1. **Bash Script Command**
+ - Command to run on CCTV server
+ - Installs background daemon
+ - Configures streaming to Cloudflare Realtime SFU
+ - Daemon starts on system startup
+
+2. **API Key Generation**
+ - Unique API key generated for CCTV component
+ - Embedded in bash script
+
+### 6. Builder Pattern (Durable Objects)
+
+The signup flow uses a **Builder pattern** implemented with Durable Objects:
+
+**Purpose:**
+- Maintains state across multi-step signup process
+- Allows users to navigate back and forth
+- Enables changes at any step before completion
+- Fast state management without constant database writes
+
+**Why Durable Objects:**
+- Fast state access and updates
+- Maintains consistency during navigation
+- Easy to manage complex flow state
+- Persists until flow completion
+
+### 7. System Setup & Dashboard Access
+
+After all configurations are complete:
+
+1. **Background Setup**: System sets up organization infrastructure
+2. **Initial Processing**: If product scraping was selected, processing begins
+3. **Loading State**: User sees setup progress
+4. **Dashboard Redirect**: Once ready, user is redirected to dashboard
+
+### 8. Final Destination
+
+User arrives at the **Dashboard Home Page** where they can:
+- View organization overview
+- Access chat interface
+- Manage products
+- View interactions and patterns
+- Configure team members
+- Manage settings and integrations
+
+## Invited User Flow
+
+The invited user flow is simpler but crucial for multi-user organizations.
+
+### Invitation Process
+
+1. **Existing User Sends Invite**
+ - User with appropriate permissions sends email invitation
+ - Validation checks if invitee already has an organization
+ - If validation passes, invitation email is sent
+
+2. **Invitee Receives Email**
+ - Invitation email contains acceptance link
+ - Link leads to acceptance page
+
+3. **Acceptance Page**
+ - Similar to GitHub repository access flow
+ - User must explicitly accept invitation
+ - Clear display of organization details
+
+4. **Modified Signup Flow**
+ - User proceeds to standard signup (username, email, password)
+ - **Organization creation step is skipped** (1:1 mapping applies)
+ - User automatically joins inviting organization
+ - Redirected directly to dashboard
+
+**Key Difference**: Invited users skip organization creation because the 1:1 User:Organization mapping means they automatically join the organization that invited them.
+
+## Related Flows
+
+### Returning User Login
+
+Returning users with existing accounts follow a different flow:
+- Standard login process
+- Session validation
+- Direct dashboard access
+- No organization creation or configuration
+
+### Team Management
+
+After signup, organization owners/admins can:
+- Invite additional team members
+- Set permission levels for users
+- Manage team member access
+- Remove team members if needed
+
+**[→ Learn more about User Permission Levels](../reference/user-permissions.md)**
diff --git a/docs/features/website-interaction-tracking.md b/docs/features/website-interaction-tracking.md
new file mode 100644
index 0000000..5fe43d0
--- /dev/null
+++ b/docs/features/website-interaction-tracking.md
@@ -0,0 +1,453 @@
+---
+sidebar_position: 1
+---
+
+# Website Interaction Tracking
+
+## Overview
+
+The Website Interaction Tracking system captures user behavior on client applications (web, mobile, desktop) and processes it into actionable insights. This is the **Phase 1 component** of CROW and the current focus for development.
+
+## JavaScript SDK
+
+CROW provides a **JavaScript SDK** for easy integration into web, mobile (React Native), and desktop (Electron) applications.
+
+### Supported Platforms
+
+- **Web**: Any website or web application
+- **Mobile**: React Native applications (with DOM-like structure)
+- **Desktop**: Electron applications (Chromium-based)
+
+The SDK works with any platform that has a DOM setup, making it versatile across user interfaces.
+
+### Installation
+
+```bash
+# npm
+npm install @crow/tracking-sdk
+
+# pnpm
+pnpm add @crow/tracking-sdk
+
+# bun
+bun add @crow/tracking-sdk
+```
+
+### Basic Setup
+
+```javascript
+// React Application
+import { CROWTracker } from '@crow/tracking-sdk';
+
+const tracker = new CROWTracker({
+ apiKey: 'your-api-key-here',
+ endpoint: 'https://api.crow.example.com'
+});
+
+// SDK automatically tracks:
+// - Page views
+// - Clicks
+// - Form interactions
+// - Product views
+// - Custom events
+```
+
+### Platform-Specific Examples
+
+#### React Native
+
+```javascript
+// React Native Application
+import { CROWTracker } from '@crow/tracking-sdk';
+
+const tracker = new CROWTracker({
+ apiKey: 'your-api-key-here',
+ endpoint: 'https://api.crow.example.com',
+ platform: 'react-native'
+});
+
+// Works with React Native's component structure
+```
+
+#### Electron
+
+```javascript
+// Electron Application (Main or Renderer Process)
+import { CROWTracker } from '@crow/tracking-sdk';
+
+const tracker = new CROWTracker({
+ apiKey: 'your-api-key-here',
+ endpoint: 'https://api.crow.example.com',
+ platform: 'electron'
+});
+
+// Works with Electron's Chromium-based rendering
+```
+
+### SDK Features
+
+The CROW tracking SDK is designed to be lightweight and non-intrusive:
+
+- **Lightweight Wrapper**: Minimal bundle size impact (< 10KB gzipped)
+- **Auto-Tracking**: Automatic capture of common events
+- **Custom Events**: Support for application-specific tracking
+- **Batching**: Efficient event batching to reduce network calls
+- **Offline Support**: Queue events when offline, sync when online
+- **Privacy Controls**: GDPR/CCPA compliance features
+- **No Dependencies**: Zero external dependencies
+- **TypeScript Support**: Full TypeScript definitions included
+
+### Tracked Events
+
+#### Automatic Tracking
+
+The SDK automatically tracks:
+
+1. **Page Views**
+ - URL, title, referrer
+ - Timestamp and session ID
+ - Viewport size and device type
+
+2. **Clicks**
+ - Element clicked (button, link, etc.)
+ - Element attributes and text content
+ - Position on page
+
+3. **Form Interactions**
+ - Form submissions
+ - Field focus/blur events
+ - Validation errors
+
+4. **Product Views**
+ - Product ID and name
+ - View duration
+ - Scroll depth
+
+5. **Performance Metrics**
+ - Page load time
+ - Time to interactive
+ - Core Web Vitals
+
+#### Custom Events
+
+Developers can track custom events:
+
+```javascript
+tracker.track('purchase_completed', {
+ productId: '12345',
+ amount: 99.99,
+ currency: 'USD'
+});
+```
+
+## Ingestion Service Architecture
+
+```mermaid
+flowchart TD
+ A[Client Application
Web/Mobile/Desktop] --> B[JS SDK]
+ B --> C[API Gateway]
+ C --> D[Web Ingest Worker]
+ D --> E[Durable Object
Session State]
+ E --> F{Inactivity Check}
+ F -->|< 1 hour| E
+ F -->|≥ 1 hour| G[Cloudflare Queues]
+ G --> H[Interaction Service]
+ H --> I[Generate Insights]
+ I --> J[Vectorize
Embeddings]
+ I --> K[D1 Database
Metadata]
+ I --> L[Analytics Service
Billing]
+```
+
+## Session Management with Durable Objects
+
+### How It Works
+
+1. **SDK Sends Events**: User interactions sent to API Gateway
+2. **Gateway Routes**: Requests routed to Web Ingest Worker
+3. **Durable Object Storage**: Events stored in Durable Object per session
+4. **Inactivity Alarm**: Durable Object sets alarm for 1 hour
+5. **Alarm Triggers**: After 1 hour of inactivity, alarm fires
+6. **Queue Dispatch**: Session data sent to Interaction Service queue
+7. **Processing**: Interaction Service processes session
+
+### Why Durable Objects?
+
+- **Fast State Management**: Instant read/write without database roundtrips
+- **Automatic Alarms**: Built-in alarm system for time-based triggers
+- **Session Isolation**: Each session has independent state
+- **Scalability**: Automatically scales with traffic
+- **Consistency**: Strong consistency guarantees
+
+### Durable Objects vs Traditional Session Storage
+
+| Capability | Durable Objects | Traditional Redis |
+|------------|-----------------|-------------------|
+| **Latency** | Low-latency access from Workers | Depends on Redis region vs client |
+| **Consistency** | Strong consistency per object | Eventually consistent (typical) |
+| **Scaling** | Automatic | Manual sharding |
+| **Billing** | Per request + duration | Instance-based |
+
+### Session Definition
+
+**Web Session**: A period of user activity ending after **1 hour of inactivity**. When 1 hour passes without new events, the session is considered complete and sent for processing.
+
+## Web Ingest Worker
+
+### Service Details
+
+**Service Name**: `web-ingest-worker`
+
+**Technology**: Cloudflare Workers (TypeScript) with Durable Objects
+
+**Deployment**: Cloudflare Workers edge network
+
+### Why Cloudflare Workers?
+
+- **Global Edge Network**: Ingestion happens at 300+ edge locations
+- **Sub-50ms Latency**: Response times under 50ms globally
+- **Instant Scaling**: Handles traffic spikes automatically
+- **Zero Cold Starts**: V8 isolates start in milliseconds
+- **Integrated Storage**: Direct access to Durable Objects, D1, and Queues
+- **Durable Objects**: Perfect for session state management with alarms
+
+### Ingestion Process
+
+1. **Receive Events**: SDK sends batched events to nearest edge location
+2. **API Gateway**: Validates auth, converts session/API key to JWT
+3. **Web Ingest Worker**: Receives events with JWT
+4. **Durable Object**: Stores events in session-specific Durable Object
+5. **Alarm Management**: Sets/resets alarm for 1-hour inactivity
+6. **Queue Dispatch**: After alarm fires, sends session to Interaction Queue
+
+## Session Processing Pipeline
+
+```mermaid
+sequenceDiagram
+ participant SDK as JS SDK
+ participant Gateway as API Gateway
+ participant Worker as Web Ingest Worker
+ participant DO as Durable Object
+ participant Queue as Cloudflare Queues
+ participant Interaction as Interaction Service
+ participant Vec as Vectorize
+ participant Analytics as Analytics Service
+
+ SDK->>Gateway: Send Events Batch
+ Gateway->>Gateway: Validate Session/API Key
+ Gateway->>Gateway: Issue JWT
+ Gateway->>Worker: Forward with JWT
+ Worker->>DO: Store Events
+ DO->>DO: Reset Inactivity Alarm (1hr)
+
+ Note over DO: ... 1 hour passes ...
+
+ DO->>DO: Alarm Fires
+ DO->>Queue: Send Session Data
+ Queue->>Interaction: Process Session
+ Interaction->>Interaction: Analyze with Gemini AI
+ Interaction->>Vec: Store Embeddings
+ Interaction->>Analytics: Track for Billing
+```
+
+### Pipeline Stages
+
+#### 1. Event Collection
+- SDK collects user interactions
+- Batches events to reduce network calls
+- Sends to nearest edge location via API Gateway
+
+#### 2. Authentication & Routing
+- API Gateway validates session or API key
+- Converts to JWT for internal use
+- Routes to Web Ingest Worker
+
+#### 3. Durable Object Storage
+- Events stored in session-specific Durable Object
+- Alarm set for 1-hour inactivity
+- Alarm reset on each new event
+
+#### 4. Session Completion
+- After 1 hour without events, alarm fires
+- Session marked as complete
+- Session data sent to Cloudflare Queues
+
+#### 5. Async Processing Queue
+- Session IDs added to Interaction Queue
+- Queue acts as buffer between ingestion and processing
+- Enables scaling of processing layer independently
+
+#### 6. Interaction Service Processing
+- Interaction Service consumes queue messages
+- Retrieves Organization and Product context
+- Analyzes session using Gemini AI via Vercel AI SDK
+- Generates human-readable interaction records
+- Stores embeddings in Vectorize and metadata in D1
+- Notifies Analytics Service for billing
+
+## Cloudflare Workflows Processing
+
+**Cloudflare Workflows** orchestrates multi-step session processing with built-in durability.
+
+### How Workflows Work
+
+- **Durable Execution**: Steps are checkpointed automatically
+- **Retry Logic**: Built-in retries for failed steps
+- **Long-running**: Can run for extended periods without timeouts
+- **Event-driven**: Triggered by Cloudflare Queues
+
+```mermaid
+graph LR
+ A[Cloudflare Queues] --> B[Trigger Service]
+ B --> C[Start Workflow]
+ C --> D[Process Session]
+ D --> E[Generate Embeddings]
+ E --> F[Store Results]
+```
+
+### Workflow Steps
+
+- **Validate Session**: Check session data completeness
+- **Enrich Context**: Add product and organization context
+- **AI Processing**: Send to ai-processing-service
+- **Generate Embeddings**: Create vector embeddings
+- **Store Results**: Save to D1 and Vectorize
+
+## Session Understanding with AI
+
+The ai-processing-service analyzes user sessions to generate meaningful interactions.
+
+### Processing Capabilities
+
+**1. Behavior Analysis**
+- Interprets user actions
+- Identifies patterns in clicks and navigation
+- Detects user intent signals
+
+**2. Intent Detection**
+- Determines user intent (browsing, comparing, purchasing)
+- Classifies session goals
+- Predicts next actions
+
+**3. Interaction Generation**
+- Creates natural language interactions
+- Translates technical events to business insights
+- Generates human-readable summaries
+
+**4. Context Enrichment**
+- Adds product and business context
+- Links to product catalog
+- Enriches with organizational data
+
+### Example Processing
+
+**Raw Events:**
+```json
+[
+ {"type": "page_view", "url": "/products/laptop-x1"},
+ {"type": "click", "element": "add_to_cart"},
+ {"type": "page_view", "url": "/cart"},
+ {"type": "click", "element": "checkout"}
+]
+```
+
+**Generated Interaction:**
+```
+User viewed Laptop X1 product page, added item to cart, and proceeded to checkout.
+Indicates high purchase intent for Laptop X1.
+```
+
+## Data Flow
+
+### Complete Flow
+
+```mermaid
+flowchart LR
+ A[User Actions on Website] --> B[JS SDK]
+ B --> C[Ingestion Worker]
+ C --> D[D1 Session Storage]
+ D --> E[Cloudflare Queues]
+ E --> F[Workflows]
+ F --> G[ai-processing-service]
+ G --> H[Vectorize & D1]
+ H --> I[Analytics Dashboard]
+```
+
+## Integration with Data Storage
+
+The interactions generated by the session processors feed into the CROW Data Lake where they are:
+
+- **Stored as raw data in R2**: Full interaction data for archival
+- **Vectorized and indexed in Vectorize**: Enables semantic search
+- **Cataloged in D1 with metadata**: Source, timestamp, products, organization
+
+For more information, see the [Data Storage Architecture](../architecture/data-lake-architecture.md) documentation.
+
+## Privacy & Compliance
+
+### Data Privacy
+
+- **Anonymization**: Personal data can be anonymized
+- **User Consent**: SDK respects user consent preferences
+- **Data Retention**: Configurable retention policies
+- **Right to Deletion**: Support for GDPR deletion requests
+
+### Compliance Features
+
+- **GDPR**: Full GDPR compliance support
+- **CCPA**: California Consumer Privacy Act compliance
+- **Cookie Consent**: Integration with cookie consent tools
+- **Do Not Track**: Respects DNT browser settings
+
+## Performance & Reliability
+
+### Performance Metrics
+
+- **Ingestion Latency**: < 50ms (p95)
+- **Processing Latency**: < 5 minutes (queue to insights)
+- **Throughput**: 100K+ events/second
+- **Availability**: 99.9% uptime SLA
+
+### Error Handling
+
+- **Retry Logic**: Automatic retries with exponential backoff
+- **Dead Letter Queue**: Failed events moved to DLQ for investigation
+- **Monitoring**: Real-time alerts on error rates
+- **Graceful Degradation**: SDK continues to work if backend is down
+
+## API Key Management
+
+### Creating API Keys
+
+1. Organization admin creates API key in dashboard
+2. Key scoped to organization
+3. Optional domain restrictions
+4. Rate limiting per key
+
+### Security
+
+- **Encryption**: Keys encrypted at rest
+- **Rotation**: Support for key rotation
+- **Revocation**: Instant key revocation
+- **Audit Logging**: All key usage logged
+
+## Monitoring & Analytics
+
+### Real-Time Metrics
+
+- Events ingested per second
+- Session processing queue depth
+- Error rates and types
+- Geographic distribution of events
+
+### Dashboards
+
+- Organization-level analytics
+- Product interaction heatmaps
+- User journey visualization
+- Conversion funnel analysis
+
+## Related Documentation
+
+- [Data Storage Architecture](../architecture/data-lake-architecture.md) - How interaction data is stored
+- [System Architecture](../architecture/system-architecture.md) - Overall platform architecture
+- [Integration API](../architecture/integration-api.md) - API for accessing interaction data
diff --git a/docs/index.md b/docs/index.md
index 115da92..09ebef1 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -5,28 +5,86 @@ slug: /
# CROW Internal Documentation
-Welcome to the **internal documentation** for **CROW** (Cognitive Reasoning Observation Watcher) by **B3**.
+Welcome to the internal documentation for **CROW** (Cognitive Reasoning Observation Watcher) by **B3**.
## About CROW
-CROW is our internal project focused on cognitive reasoning and observation systems. This internal documentation serves as the central knowledge base for the B3 team.
+CROW is a unified customer interaction intelligence platform designed to address a fundamental challenge: customer behavior signals generated across digital storefronts, physical retail, and social media remain fragmented within isolated systems. This fragmentation prevents organizations from developing a unified understanding of shopper behavior.
-## Getting Started
+### The Problem
-This internal documentation site contains all the information you need to understand, develop, and maintain the CROW project.
+Organizations face three interconnected challenges:
-### Navigation
+1. **Collection**: Raw signals are difficult to capture comprehensively across web, in-store, and social channels
+2. **Interpretation**: Captured data lacks contextual understanding to transform into meaningful insights
+3. **Synthesis**: Insights cannot be combined into actionable patterns across channels
-Use the sidebar on the left to browse through different sections of the internal documentation.
+### The Solution
-### Contributing to Internal Documentation
+CROW consolidates multimodal interaction signals into a single, searchable natural language data layer:
-To add or update internal documentation:
+- **Web Analytics**: Lightweight JavaScript SDK captures user interactions
+- **In-Store**: CCTV footage processed through real-time video streaming with Gemini Live
+- **Social Media**: Scheduled discovery agents collect public brand mentions
-1. Edit markdown files in the `docs/` directory
-2. The site will automatically rebuild with your changes
-3. All internal documentation is version-controlled with the project
+The platform transforms raw behavioral signals into contextually enriched, human-readable interaction records. Sales, marketing, product, and operations teams can access unified customer insights through dashboards and APIs without manual cross-channel data reconciliation.
+
+### Three Core Components
+
+CROW operates through three main data collection components, deployed in phases:
+
+#### 1. Web Component (Phase 1 - Current Focus)
+The Web component provides an SDK that integrates with brand-owned applications (web, mobile via React Native, and desktop via Electron). This lightweight SDK captures user interactions, events, and behaviors across any user interface with a DOM setup. The SDK sends interaction data to our platform where it's processed and analyzed to generate insights.
+
+#### 2. Social Component (Phase 2)
+The Social component performs intelligent web searching and extraction of social media data. It analyzes company social media posts, comments, and engagement across various platforms to gather insights at a deep level, tracking public sentiment and engagement patterns.
+
+#### 3. CCTV Component (Phase 3)
+The CCTV component represents our most advanced offering. It streams CCTV footage from retail stores through Cloudflare's real-time serverless SFU using WebRTC. The streams are converted via WebRTC-to-WebSocket adapters and fed to Gemini Live for real-time analysis, providing descriptions of customer movements, behaviors, and interactions within physical spaces.
+
+### Key Differentiators
+
+- **Centralized Platform**: Single source of truth for all interaction data across channels
+- **Contextual Analysis**: Not just raw data, but interactions analyzed with full business context
+- **Pattern Recognition**: Identifies trends and patterns across all collected data
+- **Universal Value**: A data platform that can be utilized by anyone within an organization, with unlimited potential applications
+
+## Documentation Overview
+
+### Architecture
-## Need Help?
+- **[System Architecture](./architecture/system-architecture.md)** - Platform architecture on Cloudflare's edge
+- **[Frontend Architecture](./architecture/frontend-architecture.md)** - Landing and dashboard applications
+- **[Services Architecture](./architecture/microservices.md)** - Cloudflare Workers-based services
+- **[Data Storage](./architecture/data-lake-architecture.md)** - D1, R2, and Vectorize storage
+- **[Integration API](./architecture/integration-api.md)** - REST, A2A, and MCP APIs
-If you have questions or need clarification on any topic, please reach out to the B3 team.
+### Features
+
+- **[Website Tracking](./features/website-interaction-tracking.md)** - JavaScript SDK and interaction ingestion
+- **[Social Media](./features/social-media-component.md)** - AI-driven web search and social scraping
+- **[CCTV](./features/cctv-component.md)** - Real-time video analysis with Gemini Live
+- **[Product Scraping](./features/product-scraping.md)** - AI-powered product catalog scraping
+- **[Chat System](./features/chat-system.md)** - Conversational AI interface
+- **[User Signup Flow](./features/user-signup-flow.md)** - Registration and onboarding
+- **[Dashboard Features](./features/dashboard-features.md)** - Dashboard pages and functionality
+
+### Reference
+
+- **[Coding Conventions](./reference/coding-conventions.md)** - Development standards
+- **[Package Versioning](./reference/package-versioning.md)** - Zero-major versioning philosophy
+- **[User Permissions](./reference/user-permissions.md)** - Access control and permission levels
+- **[System Requirements](./reference/requirements.md)** - Functional and non-functional requirements
+- **[Compliance and Ethics](./reference/compliance-and-ethics.md)** - Privacy, legal, and ethical considerations
+
+## Getting Started
+
+Use the sidebar to navigate through documentation sections.
+
+### Contributing
+
+To update documentation:
+
+1. Edit markdown files in the `docs/` directory
+2. The site rebuilds automatically with your changes
+3. All documentation is version-controlled
diff --git a/docs/reference/_category_.json b/docs/reference/_category_.json
new file mode 100644
index 0000000..6870a56
--- /dev/null
+++ b/docs/reference/_category_.json
@@ -0,0 +1,5 @@
+{
+ "label": "Reference",
+ "position": 4,
+ "collapsed": false
+}
diff --git a/docs/reference/coding-conventions.md b/docs/reference/coding-conventions.md
new file mode 100644
index 0000000..07773ee
--- /dev/null
+++ b/docs/reference/coding-conventions.md
@@ -0,0 +1,396 @@
+---
+sidebar_position: 1
+---
+
+# Coding Conventions
+
+This document establishes the coding standards and conventions for the CROW codebase. These rules ensure consistency, readability, and maintainability across all our code.
+
+## Philosophy
+
+Our coding standards optimize for **clarity over cleverness**. Code should be self-explanatory, flat, and predictable. If you need to add a comment to explain what code does, the code needs to be rewritten.
+
+---
+
+## TypeScript/JavaScript Standards
+
+### Base Style Guide
+
+We follow the [Google TypeScript Style Guide](https://google.github.io/styleguide/tsguide.html) as our foundation, with specific overrides and additions documented below.
+
+### 1. Comments Policy: No Comments (Self-Documenting Code)
+
+**Rule:** Code must be self-documenting. Comments are considered a code smell.
+
+**Rationale:** If code requires comments to be understood, it means the code itself is unclear. Instead of adding comments, refactor the code to be more readable.
+
+**What to do instead:**
+- Use descriptive variable and function names
+- Extract complex logic into well-named functions
+- Break down large functions into smaller, focused ones
+- Use guard clauses and early returns
+
+**Exception:** Public API documentation for exported interfaces is acceptable when necessary for external consumers.
+
+```typescript
+// BAD: Using comments to explain unclear code
+function calc(x: number, y: number): number {
+ // Calculate the discount based on order total
+ const d = x > 100 ? 0.2 : 0.1
+ // Apply discount and return
+ return y - (y * d)
+}
+
+// GOOD: Self-documenting code
+function calculateDiscountedPrice(orderTotal: number, itemPrice: number): number {
+ const discountRate = orderTotal > 100 ? 0.2 : 0.1
+ const discountAmount = itemPrice * discountRate
+ return itemPrice - discountAmount
+}
+```
+
+### 2. Maximum Indentation: 1 Level
+
+**Rule:** Functions must not exceed 1 level of indentation (excluding the function body itself).
+
+**Rationale:** Deep nesting creates cognitive load. Each indentation level multiplies the number of mental states developers must track. Flat code is easier to read, test, and maintain.
+
+**Techniques to achieve this:**
+- Use guard clauses and early returns
+- Extract nested logic into separate functions
+- Use array methods (`map`, `filter`, `reduce`) instead of nested loops
+- Leverage polymorphism or lookup tables instead of nested conditionals
+
+```typescript
+// BAD: Multiple levels of nesting
+function processUser(user: User | null): string {
+ if (user) {
+ if (user.isActive) {
+ if (user.hasPermission('admin')) {
+ return 'Admin user processed'
+ } else {
+ return 'Regular user processed'
+ }
+ } else {
+ return 'Inactive user'
+ }
+ } else {
+ return 'No user found'
+ }
+}
+
+// GOOD: Guard clauses, single indentation level
+function processUser(user: User | null): string {
+ if (!user) return 'No user found'
+ if (!user.isActive) return 'Inactive user'
+ if (user.hasPermission('admin')) return 'Admin user processed'
+
+ return 'Regular user processed'
+}
+```
+
+```typescript
+// BAD: Nested loops
+function findMatchingItems(orders: Order[]): Item[] {
+ const results: Item[] = []
+ for (const order of orders) {
+ for (const item of order.items) {
+ if (item.price > 100) {
+ results.push(item)
+ }
+ }
+ }
+ return results
+}
+
+// GOOD: Functional approach with single level
+function findMatchingItems(orders: Order[]): Item[] {
+ return orders
+ .flatMap(order => order.items)
+ .filter(item => item.price > 100)
+}
+```
+
+### 3. Paradigm: Functional Programming First
+
+**Rule:** Default to functional programming patterns. Object-oriented approaches are a last resort, rarely needed.
+
+**Rationale:** FP promotes immutability, predictability, and testability. Pure functions are easier to reason about, test, and debug than stateful objects.
+
+**Prefer:**
+- Pure functions (same input → same output, no side effects)
+- Immutable data structures
+- Function composition
+- Data transformations over data mutation
+
+**Use OO only when:**
+- Managing complex lifecycle or state (e.g., connection pools, streams)
+- Implementing required interfaces from external libraries
+- Creating boundary abstractions (DB clients, HTTP clients)
+
+```typescript
+// BAD: Unnecessary OOP approach
+class UserValidator {
+ private errors: string[] = []
+
+ validate(user: User): boolean {
+ this.errors = []
+ if (!user.email) this.errors.push('Email required')
+ if (!user.name) this.errors.push('Name required')
+ return this.errors.length === 0
+ }
+
+ getErrors(): string[] {
+ return this.errors
+ }
+}
+
+// GOOD: Functional approach
+type ValidationResult = {
+ isValid: boolean
+ errors: string[]
+}
+
+function validateUser(user: User): ValidationResult {
+ const errors: string[] = []
+ if (!user.email) errors.push('Email required')
+ if (!user.name) errors.push('Name required')
+
+ return {
+ isValid: errors.length === 0,
+ errors
+ }
+}
+```
+
+### 4. Composition Over Inheritance
+
+**Rule:** Always prefer composition over inheritance. Inheritance is only acceptable for true "is-a" relationships.
+
+**Rationale:** Inheritance creates tight coupling and fragile base class problems. Composition provides flexibility and clearer dependencies.
+
+```typescript
+// BAD: Inheritance for code reuse
+class Logger {
+ log(message: string): void {
+ console.log(message)
+ }
+}
+
+class UserService extends Logger {
+ createUser(name: string): void {
+ this.log(`Creating user: ${name}`)
+ }
+}
+
+// GOOD: Composition
+type Logger = {
+ log: (message: string) => void
+}
+
+const createLogger = (): Logger => ({
+ log: (message) => console.log(message)
+})
+
+type UserService = {
+ createUser: (name: string) => void
+}
+
+const createUserService = (logger: Logger): UserService => ({
+ createUser: (name) => {
+ logger.log(`Creating user: ${name}`)
+ }
+})
+```
+
+### 5. Architecture: Layer-Based Structure
+
+**Rule:** Organize code by architectural layers (horizontal slicing).
+
+**Structure:**
+```
+src/
+├── controllers/ # HTTP handlers, route handlers
+├── services/ # Business logic
+├── repositories/ # Data access
+├── models/ # Data types and schemas
+├── utils/ # Shared utilities
+└── config/ # Configuration
+```
+
+**Rationale:** Layer-based architecture makes the system structure immediately clear and enforces separation of concerns.
+
+### 6. Error Handling: Exceptions at Boundaries
+
+**Rule:** Throw exceptions only at integration boundaries. Add context when throwing.
+
+**Guidelines:**
+- Throw exceptions at boundaries (HTTP, DB, external APIs)
+- Never swallow errors silently
+- Wrap exceptions with context
+- Log errors exactly once (at the boundary)
+- Let errors bubble up with meaningful context
+
+```typescript
+// GOOD: Exception handling at boundaries
+async function fetchUserFromDatabase(userId: string): Promise {
+ try {
+ const result = await db.query('SELECT * FROM users WHERE id = ?', [userId])
+ return result.rows[0]
+ } catch (error) {
+ throw new Error(`Failed to fetch user ${userId}: ${error.message}`)
+ }
+}
+
+// GOOD: Letting errors bubble with context
+async function getUserProfile(userId: string): Promise {
+ const user = await fetchUserFromDatabase(userId)
+ const profile = transformUserToProfile(user)
+ return profile
+}
+```
+
+### 7. Naming: Long Descriptive Names
+
+**Rule:** Optimize for reading, not typing. Names should be long and descriptive.
+
+**Guidelines:**
+- Use full words, avoid abbreviations
+- Boolean variables: prefix with `is`, `has`, `should`, `can`
+- Functions: use verb prefixes (`get`, `fetch`, `create`, `update`, `delete`, `calculate`, `transform`, `validate`)
+- Avoid vague names like `data`, `info`, `manager`, `util`, `handler`
+
+```typescript
+// BAD: Unclear, abbreviated names
+function proc(u: User): void {
+ const d = getData(u)
+ handle(d)
+}
+
+// GOOD: Clear, descriptive names
+function processUserRegistration(user: User): void {
+ const userPreferences = getUserPreferences(user)
+ sendWelcomeEmail(userPreferences)
+}
+```
+
+**Naming conventions:**
+```typescript
+// Booleans
+const isAuthenticated = true
+const hasPermission = false
+const shouldRedirect = true
+const canEditProfile = false
+
+// Functions
+function getUserById(id: string): User
+function createNewOrder(items: Item[]): Order
+function calculateTotalPrice(items: Item[]): number
+function transformUserToDTO(user: User): UserDTO
+function validateEmailFormat(email: string): boolean
+```
+
+### 8. Function Size: Maximum 20-40 Lines
+
+**Rule:** Functions should be small, typically 20-40 lines maximum.
+
+**Rationale:** Small functions are easier to understand, test, and maintain. If a function is longer, it likely has multiple responsibilities.
+
+**How to achieve this:**
+- Extract helper functions
+- Use array methods for collections
+- Apply the single responsibility principle
+- Break complex logic into named steps
+
+```typescript
+// BAD: Long, multi-responsibility function
+function processOrder(order: Order): void {
+ // Validate order (8 lines)
+ if (!order.items || order.items.length === 0) throw new Error('No items')
+ if (!order.customerId) throw new Error('No customer')
+ // ... more validation
+
+ // Calculate totals (10 lines)
+ let subtotal = 0
+ for (const item of order.items) {
+ subtotal += item.price * item.quantity
+ }
+ // ... more calculation
+
+ // Save to database (8 lines)
+ // ... database operations
+
+ // Send notifications (8 lines)
+ // ... email sending
+}
+
+// GOOD: Small, focused functions
+function processOrder(order: Order): void {
+ validateOrder(order)
+ const orderTotal = calculateOrderTotal(order)
+ saveOrderToDatabase(order, orderTotal)
+ sendOrderConfirmationEmail(order)
+}
+
+function validateOrder(order: Order): void {
+ if (!order.items || order.items.length === 0) throw new Error('No items')
+ if (!order.customerId) throw new Error('No customer')
+}
+
+function calculateOrderTotal(order: Order): number {
+ return order.items.reduce((sum, item) => sum + (item.price * item.quantity), 0)
+}
+```
+
+### 9. Testing: Coverage Thresholds Required
+
+**Rule:** Maintain minimum code coverage thresholds. PRs must maintain or improve coverage.
+
+**Requirements:**
+- Business logic functions must have tests
+- Aim for meaningful coverage, not just hitting numbers
+- Focus on testing behavior, not implementation details
+- Test edge cases and error conditions
+
+**What to test:**
+- Business logic and calculations
+- Data transformations
+- Validation functions
+- Error handling paths
+
+**What not to test:**
+- Simple getters/setters
+- Framework glue code
+- Third-party library wrappers (unless adding logic)
+
+---
+
+## Commit Messages
+
+We use [commitlint](https://github.com/conventional-changelog/commitlint) for consistent commit formatting.
+
+**Format:** `: `
+
+**Types:** `feat`, `fix`, `docs`, `style`, `refactor`, `test`, `chore`
+
+**Examples:**
+```
+feat: add authentication
+fix: resolve timeout issue
+docs: update readme
+refactor: extract user validation logic
+test: add coverage for order processing
+```
+
+---
+
+## Enforcement
+
+These standards are enforced through:
+- Code reviews (all PRs require approval)
+- ESLint configuration based on `@antfu/eslint-config`
+- Prettier for formatting
+- Pre-commit hooks via Husky
+- CI pipeline checks
+
+**Remember:** These rules exist to make our codebase more maintainable and easier to work with. When in doubt, optimize for the person reading your code six months from now.
diff --git a/docs/reference/compliance-and-ethics.md b/docs/reference/compliance-and-ethics.md
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--- /dev/null
+++ b/docs/reference/compliance-and-ethics.md
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+---
+sidebar_position: 5
+---
+
+# Compliance and Ethics
+
+## Overview
+
+CROW collects, analyzes, and distributes behavioral data from websites, social media, and CCTV. Each data source presents distinct considerations for privacy, compliance, and trust. This document outlines the key issues and how the platform addresses them.
+
+## Social Considerations
+
+### Trust and Perception
+
+Customers may perceive behavior monitoring as invasive surveillance, potentially eroding brand trust.
+
+**Mitigations:**
+
+- **Transparency**: Organizations should display clear signage about behavior analysis with contact information
+- **Aggregated Insights**: Data provides generalized patterns rather than individual customer tracking
+- **Behavioral Focus**: CCTV analysis describes observed behavior, not inferred preferences or predictions
+
+## Legal Considerations
+
+### GDPR Compliance
+
+Behavioral data may constitute personal data under GDPR Article 4(1) if it enables identification.
+
+**Mitigations:**
+
+| Principle | Implementation |
+|-----------|----------------|
+| **Data Minimization** | Collect only necessary data per channel |
+| **Session Abstraction** | Data operates at session level, not per-user |
+| **Retention Controls** | Organizations configure automated deletion policies |
+| **Access Controls** | Role-based access with audit logging |
+| **Right to Erasure** | Complete data deletion available via settings |
+
+### Social Media Terms of Service
+
+Unauthorized scraping or content storage violates platform terms.
+
+**Mitigations:**
+
+- **API-First Collection**: Use official platform APIs and developer access where available
+- **Attribution Preservation**: Maintain links to source posts for transparency
+- **Public Data Only**: Only process publicly available content
+- **Rate Limit Compliance**: Respect platform rate limits and ToS
+
+## Ethical Considerations
+
+### AI Reliability
+
+Generative AI models can produce confident but incorrect outputs, potentially misleading business decisions.
+
+**Mitigations:**
+
+- **Evidence Traceability**: Insights include links to source events for verification
+- **Confidence Scoring**: Outputs include confidence indicators; low confidence insights are flagged
+- **Human in the Loop**: CROW positions as decision support, not automation
+
+### Privacy by Design
+
+CCTV processing follows privacy-first principles:
+
+- Real-time video analysis via Gemini Live API
+- No persistent video storage
+- Raw footage never saved to platform storage
+- Only behavioral insights retained
+
+## Professional Considerations
+
+### Security
+
+Multi-component platforms present expanded attack surfaces.
+
+**Mitigations:**
+
+| Control | Implementation |
+|---------|----------------|
+| **API Key Lifecycle** | Keys support expiration, scoped permissions, revocation |
+| **Rate Limiting** | Per-key and per-IP limits detect abnormal usage |
+| **Audit Logging** | All sensitive operations logged immutably |
+| **Encrypted Transport** | TLS for external, mTLS for internal communication |
+
+### Incident Response
+
+The platform maintains documented procedures for:
+
+- Detection and triage
+- Containment and isolation
+- Investigation and remediation
+- Post-incident review
+
+## Data Collection Ethics
+
+### Web Interactions
+
+- SDK respects user consent preferences
+- Integration with cookie consent tools
+- DNT (Do Not Track) browser settings honored
+- Configurable retention policies
+
+### Social Media
+
+- Public data only (no private account access)
+- No personal data collection
+- Ethical scraping with proper rate limiting
+- robots.txt compliance
+
+### CCTV
+
+- Selective camera streaming (not all cameras required)
+- Privacy zones can be masked or excluded
+- Focus on behavior patterns, not identification
+- Opt-in design (cameras explicitly configured)
+
+## Compliance Features
+
+### Data Subject Rights
+
+- **Access**: Users can view collected data
+- **Deletion**: Organization-level data clearing via settings
+- **Portability**: Export functionality for data transfer
+
+### Audit Capabilities
+
+- All access logged with timestamps
+- Permission changes tracked
+- API key usage recorded
+- Compliance-ready audit trails
+
+## Shared Responsibility Model
+
+CROW operates under a shared responsibility model:
+
+| Party | Responsibility |
+|-------|----------------|
+| **Platform (CROW)** | Technical controls, data security, privacy-preserving architecture |
+| **Organization** | Legal compliance, customer transparency, appropriate use |
+| **Users** | Human oversight of AI insights, responsible decision-making |
+
+## Related Documentation
+
+- [User Permissions](./user-permissions.md) - Access control implementation
+- [System Architecture](../architecture/system-architecture.md) - Security architecture
+- [CCTV Component](../features/cctv-component.md) - Privacy and compliance features
+- [Social Media Component](../features/social-media-component.md) - Rate limiting and ToS compliance
diff --git a/docs/reference/logging-standards.md b/docs/reference/logging-standards.md
new file mode 100644
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--- /dev/null
+++ b/docs/reference/logging-standards.md
@@ -0,0 +1,97 @@
+---
+sidebar_position: 6
+---
+
+# Logging Standards
+
+This document establishes the logging standards and best practices for the CROW platform. Consistent, structured logging is critical for debugging, monitoring, security auditing, and compliance tracking.
+
+## Philosophy
+
+Our logging approach prioritizes:
+
+- **Structured data**: All logs use structured formats (JSON) for easy parsing and analysis
+- **Meaningful context**: Include relevant contextual information without over-logging
+- **Security**: Never log sensitive data (passwords, tokens, PII)
+- **Performance**: Logging should not significantly impact application performance
+
+## Log Formatting
+
+We follow industry best practices for log formatting and structure. The platform streams structured logs to Axiom for centralized analysis and long-term retention.
+
+### Reference Guide
+
+For comprehensive guidance on log formatting, we follow the standards outlined in:
+
+**[BetterStack Logging Guide: Log Formatting](https://betterstack.com/community/guides/logging/log-formatting/?utm_source=chatgpt.com)**
+
+This guide covers:
+
+- Structured logging fundamentals
+- JSON log formatting
+- Log levels and their appropriate use
+- Contextual information best practices
+- Performance considerations
+
+## Implementation
+
+### Log Levels
+
+Use appropriate log levels for different types of events:
+
+- **ERROR**: System errors and exceptions that require attention
+- **WARN**: Warning conditions that should be reviewed but don't prevent operation
+- **INFO**: General informational messages about system operation
+- **DEBUG**: Detailed information for debugging purposes (use sparingly in production)
+
+### Structured Format
+
+All logs must use structured JSON format with consistent field names:
+
+```json
+{
+ "timestamp": "2024-02-15T10:52:33.392Z",
+ "level": "INFO",
+ "service": "api-gateway",
+ "message": "Request processed successfully",
+ "requestId": "abc-123-def",
+ "userId": "user-456",
+ "duration": 125,
+ "statusCode": 200
+}
+```
+
+### Context Requirements
+
+Include relevant context in all logs:
+
+- **Request ID**: Trace requests across services
+- **User ID**: (when applicable) Associate actions with users for audit trails
+- **Service name**: Identify the source service
+- **Duration**: For performance monitoring
+- **Error details**: Full error messages and stack traces for failures
+
+### Security
+
+**Never log sensitive information:**
+
+- Passwords or authentication credentials
+- API keys or tokens
+- Credit card numbers or payment information
+- Personal identification numbers (SSN, passport, etc.)
+- Full email addresses in non-audit logs (use hashed or truncated versions)
+
+## Monitoring and Analysis
+
+All structured logs stream to **Axiom** for:
+
+- Real-time debugging and tracing
+- Audit trail compliance
+- Performance analysis and bottleneck identification
+- Long-term retention and historical analysis
+
+## Related Documentation
+
+- [Microservices Architecture - Logging Section](../architecture/microservices.md#logging)
+- [Requirements - Structured Logging (FR37)](./requirements.md)
+- [Coding Conventions - Error Handling](./coding-conventions.md#6-error-handling-exceptions-at-boundaries)
diff --git a/docs/reference/package-versioning.md b/docs/reference/package-versioning.md
new file mode 100644
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--- /dev/null
+++ b/docs/reference/package-versioning.md
@@ -0,0 +1,117 @@
+---
+sidebar_position: 2
+---
+
+# Package Versioning
+
+## Overview
+
+We follow a **Zero-Major Versioning** philosophy, which is a deliberate variation of [Semantic Versioning (SemVer)](https://semver.org/). This approach keeps the major version permanently at `0` while using the middle and last digits differently than traditional SemVer.
+
+## The `0.Y.Z` Format
+
+Our version format is: **`0.Y.Z`**
+
+| Position | Meaning | Increments When |
+|----------|---------|-----------------|
+| `0` | Epoch/Era indicator (fixed) | Never - we opt out of SemVer's major signaling |
+| `Y` | Breaking-ish changes | API changes that may break existing integrations |
+| `Z` | Everything else | New features, bug fixes, patches - all non-breaking changes |
+
+### Think of it as: `0.MAJOR.MINOR+PATCH`
+
+- **`0`** = We opt out of SemVer's normal 'major' signaling
+- **`Y`** (second number) = Breaking changes (what SemVer would put in MAJOR)
+- **`Z`** (third number) = Features and fixes combined
+
+## Why Zero-Major?
+
+The Zero-Major approach avoids the "marketing weight" of major version bumps (v1 → v2 → v3) while still communicating breaking changes effectively. It acknowledges that:
+
+1. **Major version changes carry psychological weight** - jumping from v1 to v2 suggests a major overhaul
+2. **Breaking changes are normal** - they shouldn't require a "major release marketing event"
+3. **Simplicity** - one stream for breaking changes, one stream for everything else
+
+## Version Bump Examples
+
+### Non-Breaking Changes (Bump Z)
+
+For features, fixes, patches, and any backward-compatible changes:
+
+```
+0.65.3 → 0.65.4 (bug fix)
+0.65.4 → 0.65.5 (new feature)
+0.65.5 → 0.65.6 (documentation update)
+```
+
+### Breaking Changes (Bump Y, Reset Z)
+
+For API changes, deprecations, or anything that might break existing integrations:
+
+```
+0.65.3 → 0.66.0 (breaking API change)
+0.66.0 → 0.67.0 (another breaking change)
+```
+
+## Decision Flowchart
+
+```mermaid
+flowchart TD
+ A[New Release] --> B{Does this change break
existing integrations?}
+ B -->|Yes| C[Bump Y, Reset Z to 0]
+ B -->|No| D[Bump Z]
+ B -->|Unsure| E{Could it break
someone's workflow?}
+ E -->|Yes| C
+ E -->|No| D
+
+ C --> F["0.65.3 → 0.66.0"]
+ D --> G["0.65.3 → 0.65.4"]
+
+ style A fill:#e1f5e1,stroke:#2d5016,color:#000
+ style B fill:#fff3cd,stroke:#856404,color:#000
+ style E fill:#fff3cd,stroke:#856404,color:#000
+ style C fill:#f8d7da,stroke:#842029,color:#000
+ style D fill:#d1e7dd,stroke:#0f5132,color:#000
+ style F fill:#cfe2ff,stroke:#084298,color:#000
+ style G fill:#cfe2ff,stroke:#084298,color:#000
+```
+
+## Practical Guidelines
+
+### What counts as "breaking"?
+
+- Removing or renaming public API endpoints
+- Changing required parameters or their types
+- Modifying response formats in incompatible ways
+- Removing features that consumers might depend on
+- Changes to authentication or authorization behavior
+
+### What counts as "non-breaking"?
+
+- Adding new API endpoints
+- Adding optional parameters
+- Bug fixes that don't change expected behavior
+- Performance improvements
+- Adding new features
+- Documentation updates
+- Internal refactoring
+
+## Comparison with Traditional SemVer
+
+| Aspect | Traditional SemVer | Our Zero-Major |
+|--------|-------------------|----------------|
+| Format | `MAJOR.MINOR.PATCH` | `0.Y.Z` |
+| Breaking changes | Bump MAJOR | Bump Y |
+| New features | Bump MINOR | Bump Z |
+| Bug fixes | Bump PATCH | Bump Z |
+| Major version | Changes frequently | Always 0 |
+
+## Summary
+
+In Zero-Major Versioning:
+
+1. The **first digit is always `0`** - we opt out of major version signaling
+2. The **second digit (`Y`) signals breaking changes** - bump it when you might break something
+3. The **third digit (`Z`) is everything else** - features and fixes share this counter
+
+This approach gives us the benefits of communicating breaking changes without the overhead of managing major versions.
diff --git a/docs/reference/requirements.md b/docs/reference/requirements.md
new file mode 100644
index 0000000..ca2d6a6
--- /dev/null
+++ b/docs/reference/requirements.md
@@ -0,0 +1,124 @@
+---
+sidebar_position: 4
+---
+
+# System Requirements
+
+## Overview
+
+This document outlines the core functional and non-functional requirements for the CROW platform. These requirements guide development priorities and ensure the platform meets its intended capabilities.
+
+## Functional Requirements
+
+### Critical Priority
+
+Requirements essential for core platform functionality.
+
+| ID | Requirement | Description |
+|----|-------------|-------------|
+| FR1 | Web Interaction Capturing | Capture user events (clicks, movements, snapshots) via JavaScript SDK |
+| FR2 | Session Management | Establish sessions with 1-hour inactivity timeout, auto-publish to queue |
+| FR3 | Interaction Processing | Process sessions via Interaction Service to generate structured records |
+| FR4 | Interaction Visualization | Display interaction records in dashboard |
+| FR10 | User Authentication | Session-based auth with credential validation and secure token storage |
+| FR11 | Organization Creation | Enable new users to establish organizations during signup |
+| FR12 | Team Invitations | Support email-based team member invitations |
+| FR13 | Product Import | Support URL scraping and CSV upload for product onboarding |
+| FR14 | Component Selection | Enable selection of components (Web, Social, CCTV) during setup |
+| FR16 | API Key Management | Generate, store, and manage API keys with expiration and scoping |
+| FR17 | Dashboard Navigation | Provide core pages: Overview, Chat, Insights, Interactions, Team, Settings |
+| FR18 | AI Chat Interface | Natural language queries with contextual responses and confidence indicators |
+| FR19 | Usage Tracking | Track interactions and patterns for billing and analytics |
+
+### Desirable Priority
+
+Requirements that enhance platform capabilities.
+
+| ID | Requirement | Description |
+|----|-------------|-------------|
+| FR5 | Product Refinement | Enable users to modify and enhance scraped product details |
+| FR6 | Advanced Filtering | Support filtering by product, date range, interaction type, and channel |
+| FR7 | CCTV Ingestion | Stream video via WebRTC to Cloudflare Realtime, analyze with Gemini Live |
+| FR9 | Social Monitoring | AI-generated web searches and social media link scraping |
+| FR21 | Public Rate Limiting | IP-based JWT issuance with rate limiting for public endpoints |
+| FR22 | Pattern Detection | Daily cron jobs aggregating interactions into patterns (day, week, month, year) |
+| FR23 | Role-Based Access | Granular permission toggles for features and data access |
+| FR25 | MCP Server | Expose data via Model Context Protocol for LLM integrations |
+| FR26 | A2A Protocol | Agent-to-Agent interface for autonomous AI agent access |
+| FR28 | REST API | OpenAPI 3.1 compliant endpoints with pagination, filtering, sorting |
+| FR31 | Multi-Agent Extraction | Agent orchestration for automated product catalog extraction |
+| FR34 | AI Gateway | Route LLM requests through Cloudflare AI Gateway for caching and analytics |
+| FR36 | Metrics Collection | Edge-native metrics via Cloudflare Analytics Engine |
+| FR37 | Structured Logging | Stream logs to Axiom for analysis and audit trails |
+| FR38 | CI/CD Pipeline | Automated linting, testing, and deployment via GitHub Actions |
+
+### Luxury Priority
+
+Requirements for future optimization.
+
+| ID | Requirement | Description |
+|----|-------------|-------------|
+| FR8 | Multi-Camera Composite | Combine multiple camera angles into single high-resolution stream |
+| FR30 | GraphQL API | Flexible querying with real-time subscriptions |
+
+## Non-Functional Requirements
+
+### Scalability
+
+The system scales independently across multiple dimensions:
+
+- **Organizations**: 1:1 user-organization mapping enables clean data partitioning and future sharding
+- **Users**: Stateless microservices on Cloudflare Workers support horizontal scaling
+- **Data Volume**: Queue-based processing decouples ingestion from consumption, allowing independent scaling
+
+High-traffic services (web ingestion) scale independently from query-heavy services (dashboard) without mutual impact.
+
+### Performance
+
+The platform prioritizes responsive ingestion and efficient processing:
+
+- **Ingestion Latency**: < 50ms response time for SDK event batches
+- **Processing**: AI-intensive operations execute asynchronously via Cloudflare Queues
+- **Database**: Indexing on frequent query columns with API Gateway caching
+- **Global Distribution**: Edge deployment across 300+ Cloudflare locations
+
+### Security
+
+Layered security controls across communication, authentication, and data:
+
+- **Transport**: HTTPS with TLS for client communication, mTLS for service-to-service
+- **Authentication**: Session-based auth for users, API keys for integrations
+- **Authorization**: JWT tokens for internal service communication
+- **API Keys**: Configurable expiration, revocation, and permission scoping
+- **CCTV Privacy**: Real-time processing via Gemini Live with no persistent video storage
+
+### Maintainability
+
+Efficient development through modular architecture:
+
+- **Microservices**: Independent codebases and deployment pipelines per service
+- **Migrations**: Version-controlled database schema changes
+- **Conventions**: TypeScript across all services with consistent naming patterns
+- **Documentation**: Comprehensive internal docs with architecture decisions
+
+## Requirement Traceability
+
+| Component | Primary Requirements |
+|-----------|---------------------|
+| Web SDK | FR1, FR2 |
+| Social Worker | FR9 |
+| CCTV Worker | FR7, FR8 |
+| Interaction Service | FR3, FR4 |
+| Pattern Service | FR22 |
+| Product Service | FR5, FR13, FR31 |
+| Auth Service | FR10, FR16, FR21 |
+| Chat Service | FR18 |
+| MCP Server | FR25 |
+| A2A Service | FR26 |
+| Dashboard | FR4, FR6, FR17, FR19 |
+
+## Related Documentation
+
+- [System Architecture](../architecture/system-architecture.md) - How requirements map to architecture
+- [Services Architecture](../architecture/microservices.md) - Service-level implementation
+- [User Permissions](./user-permissions.md) - Permission requirements (FR23)
diff --git a/docs/reference/user-permissions.md b/docs/reference/user-permissions.md
new file mode 100644
index 0000000..57451b5
--- /dev/null
+++ b/docs/reference/user-permissions.md
@@ -0,0 +1,231 @@
+---
+sidebar_position: 3
+---
+
+# User Permission Levels
+
+## Overview
+
+CROW implements a permission-based access control system that allows fine-grained control over what users and API keys can access. This is critical for a data platform where different team members may need different levels of access to sensitive interaction and pattern data.
+
+## Permission Model
+
+CROW uses a **toggle-based permission system** rather than traditional role-based access control (RBAC). This provides flexibility for organizations to create custom access patterns for their team members.
+
+## API Key Permissions
+
+API keys have simple on/off toggles for data access:
+
+### Interactions Permission
+- **On**: API key can access interaction data
+- **Off**: API key cannot access interaction data
+
+### Patterns Permission
+- **On**: API key can access pattern data
+- **Off**: API key cannot access pattern data
+
+**Use Cases:**
+- External integrations that only need read access to specific data types
+- Developer testing with limited scope
+- Third-party analytics tools with restricted access
+- Audit and compliance requirements
+
+## User Permissions
+
+User permissions are more granular, with specific controls for different features.
+
+### Chat Access
+
+Chat access has **constraint-based permissions**:
+
+#### Duration Constraint
+- **Minimum**: 1 year of data
+- **Configuration**: Admin can set minimum duration (e.g., 1yr, 6mo, 3mo)
+- **Purpose**: Limit historical data access for users
+
+#### Component Constraint
+- **Minimum**: 1 component access required
+- **Options**: Web, Social, CCTV
+- **Configuration**: Admin selects which components user can query
+- **Purpose**: Restrict data source access based on role
+
+**Example Configurations:**
+- Sales team: Web + Social components, 6 months duration
+- Executive: All components, all-time duration
+- Support team: Web component only, 3 months duration
+
+### Feature Access Toggles
+
+All other features use simple on/off toggles:
+
+- **Interactions**: Can view raw interaction data
+- **Patterns**: Can view pattern data
+- **Teams**: Can manage team members and invitations
+- **API Keys**: Can create and manage API keys
+- **Billing**: Can view billing and analytics
+- **Settings**: Can access organization settings
+- **Notifications**: Can view notifications (typically always on)
+- **Integrations**: Can configure component integrations
+- **Product Management**: Can manage product catalog
+
+## Permission Management
+
+### Setting Permissions
+
+Organization admins and users with **Teams** permission can:
+1. Invite new team members
+2. Set initial permissions during invitation
+3. Modify permissions for existing users
+4. Remove team members
+
+### Permission Inheritance
+
+- **Organization Owner**: Has all permissions by default
+- **New Users**: Receive default permission set (configurable)
+- **Invited Users**: Receive permissions specified in invitation
+
+### Permission Validation
+
+Permissions are validated at multiple levels:
+1. **Frontend**: UI elements hidden based on permissions
+2. **API Gateway**: Request authorization before routing
+3. **Service Level**: Each service validates permissions
+4. **JWT Claims**: Permissions encoded in JWT for efficient validation
+
+## Default Permission Sets
+
+### Owner
+- All permissions enabled
+- Cannot be modified
+- One owner per organization
+
+### Admin
+- All feature access
+- Can manage team members
+- Can manage API keys
+- Can configure billing
+
+### Member (Default)
+- Chat access (all components, 1 year duration)
+- View interactions
+- View patterns
+- View notifications
+- No administrative access
+
+### Developer
+- Chat access (all components, 6 months)
+- View interactions
+- Manage API keys
+- Access integrations
+
+### Analyst
+- Chat access (all components, all-time)
+- View interactions
+- View patterns
+- View billing analytics
+
+## Best Practices
+
+### Principle of Least Privilege
+- Grant only necessary permissions
+- Review permissions regularly
+- Remove unused permissions
+- Audit permission changes
+
+### Permission Auditing
+- All permission changes are logged
+- Review logs for compliance
+- Monitor unusual access patterns
+- Track permission escalation
+
+### API Key Management
+- Create separate keys for different integrations
+- Use minimal permissions per key
+- Rotate keys regularly
+- Revoke unused keys immediately
+
+## Technical Implementation
+
+### Permission Storage
+
+Permissions are stored in the User Service database:
+
+```sql
+CREATE TABLE user_permissions (
+ user_id TEXT PRIMARY KEY REFERENCES users(id),
+
+ -- Chat constraints
+ chat_enabled BOOLEAN DEFAULT true,
+ chat_min_duration TEXT DEFAULT '1yr',
+ chat_components JSON DEFAULT '["web"]',
+
+ -- Feature toggles
+ interactions_enabled BOOLEAN DEFAULT true,
+ patterns_enabled BOOLEAN DEFAULT true,
+ teams_enabled BOOLEAN DEFAULT false,
+ api_keys_enabled BOOLEAN DEFAULT false,
+ billing_enabled BOOLEAN DEFAULT false,
+ settings_enabled BOOLEAN DEFAULT false,
+ notifications_enabled BOOLEAN DEFAULT true,
+ integrations_enabled BOOLEAN DEFAULT false,
+ products_enabled BOOLEAN DEFAULT false,
+
+ updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+```
+
+### JWT Claims
+
+Permissions are included in JWT tokens for efficient validation:
+
+```json
+{
+ "sub": "user_id",
+ "org": "org_id",
+ "permissions": {
+ "chat": {
+ "enabled": true,
+ "duration": "1yr",
+ "components": ["web", "social"]
+ },
+ "interactions": true,
+ "patterns": true,
+ "teams": false,
+ "apiKeys": false
+ }
+}
+```
+
+### Frontend Permission Checks
+
+```typescript
+// Example permission check in frontend
+if (user.permissions.teams) {
+ // Show team management UI
+}
+
+if (user.permissions.chat?.components.includes('cctv')) {
+ // Enable CCTV data queries in chat
+}
+```
+
+## Future Enhancements
+
+### Planned Features
+- Custom permission roles (beyond default sets)
+- Time-based permission grants (temporary access)
+- IP-based restrictions for sensitive operations
+- Two-factor authentication for permission changes
+- Automated permission reviews and alerts
+
+### Under Consideration
+- Row-level security (RLS) for data access
+- Field-level permissions (e.g., hide PII)
+- External identity provider integration
+- Permission templates for common scenarios
+
+## Related Documentation
+
+- [User Signup Flow](../features/user-signup-flow.md) - How permissions are set during signup
+- [System Architecture](../architecture/system-architecture.md) - Authentication and authorization architecture
+- [Integration API](../architecture/integration-api.md) - API key management
diff --git a/docusaurus.config.ts b/docusaurus.config.ts
index 2a56ffe..a076282 100644
--- a/docusaurus.config.ts
+++ b/docusaurus.config.ts
@@ -14,7 +14,6 @@ const config: Config = {
organizationName: "B3",
projectName: "CROW",
onBrokenLinks: "throw",
- onBrokenMarkdownLinks: "warn",
i18n: {
defaultLocale: "en",
locales: ["en"],
@@ -35,6 +34,12 @@ const config: Config = {
],
],
+ themes: ["@docusaurus/theme-mermaid"],
+
+ markdown: {
+ mermaid: true,
+ },
+
themeConfig: {
image: "img/docusaurus-social-card.jpg",
colorMode: {
diff --git a/eslint.config.mts b/eslint.config.mts
new file mode 100644
index 0000000..bf3f60f
--- /dev/null
+++ b/eslint.config.mts
@@ -0,0 +1,7 @@
+import antfu from "@antfu/eslint-config";
+
+export default antfu({
+ react: true,
+ typescript: true,
+ stylistic: false,
+});
diff --git a/package.json b/package.json
index e56cf02..08318a9 100644
--- a/package.json
+++ b/package.json
@@ -1,6 +1,7 @@
{
"name": "crow-b3-internal-docs",
"version": "0.0.1",
+ "packageManager": "bun@1.2.0",
"private": true,
"scripts": {
"docusaurus": "docusaurus",
@@ -12,22 +13,34 @@
"serve": "docusaurus serve",
"write-translations": "docusaurus write-translations",
"write-heading-ids": "docusaurus write-heading-ids",
- "typecheck": "tsc"
+ "typecheck": "tsc",
+ "prepare": "husky",
+ "lint-staged": "lint-staged"
},
+ "trustedDependencies": [
+ "@docusaurus/core",
+ "husky"
+ ],
"dependencies": {
"@docusaurus/core": "3.9.2",
"@docusaurus/preset-classic": "3.9.2",
- "@mdx-js/react": "^3.0.0",
- "clsx": "^2.0.0",
- "prism-react-renderer": "^2.3.0",
- "react": "^19.0.0",
- "react-dom": "^19.0.0"
+ "@docusaurus/theme-mermaid": "^3.9.2",
+ "@mdx-js/react": "^3.1.1",
+ "clsx": "^2.1.1",
+ "prism-react-renderer": "^2.4.1",
+ "react": "^19.2.3",
+ "react-dom": "^19.2.3"
},
"devDependencies": {
+ "@antfu/eslint-config": "^6.7.3",
+ "@commitlint/config-conventional": "^20.3.0",
"@docusaurus/module-type-aliases": "3.9.2",
"@docusaurus/tsconfig": "3.9.2",
"@docusaurus/types": "3.9.2",
- "typescript": "~5.6.2"
+ "husky": "^9.1.7",
+ "lint-staged": "^16.2.7",
+ "prettier": "^3.7.4",
+ "typescript": "~5.6.3"
},
"browserslist": {
"production": [
@@ -43,5 +56,14 @@
},
"engines": {
"node": ">=20.0"
+ },
+ "lint-staged": {
+ "*.{js,jsx,ts,tsx,mjs,cjs,mts}": [
+ "eslint --fix",
+ "prettier --write"
+ ],
+ "*.{json,md,css,scss,html,yml,yaml},.prettierrc": [
+ "prettier --write"
+ ]
}
}
diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml
deleted file mode 100644
index 3dec8b0..0000000
--- a/pnpm-lock.yaml
+++ /dev/null
@@ -1,11325 +0,0 @@
-lockfileVersion: '9.0'
-
-settings:
- autoInstallPeers: true
- excludeLinksFromLockfile: false
-
-importers:
-
- .:
- dependencies:
- '@docusaurus/core':
- specifier: 3.9.2
- version: 3.9.2(@mdx-js/react@3.1.1(@types/react@19.2.2)(react@19.2.0))(react-dom@19.2.0(react@19.2.0))(react@19.2.0)(typescript@5.6.3)
- '@docusaurus/preset-classic':
- specifier: 3.9.2
- version: 3.9.2(@algolia/client-search@5.42.0)(@mdx-js/react@3.1.1(@types/react@19.2.2)(react@19.2.0))(@types/react@19.2.2)(react-dom@19.2.0(react@19.2.0))(react@19.2.0)(search-insights@2.17.3)(typescript@5.6.3)
- '@mdx-js/react':
- specifier: ^3.0.0
- version: 3.1.1(@types/react@19.2.2)(react@19.2.0)
- clsx:
- specifier: ^2.0.0
- version: 2.1.1
- prism-react-renderer:
- specifier: ^2.3.0
- version: 2.4.1(react@19.2.0)
- react:
- specifier: ^19.0.0
- version: 19.2.0
- react-dom:
- specifier: ^19.0.0
- version: 19.2.0(react@19.2.0)
- devDependencies:
- '@docusaurus/module-type-aliases':
- specifier: 3.9.2
- version: 3.9.2(react-dom@19.2.0(react@19.2.0))(react@19.2.0)
- '@docusaurus/tsconfig':
- specifier: 3.9.2
- version: 3.9.2
- '@docusaurus/types':
- specifier: 3.9.2
- version: 3.9.2(react-dom@19.2.0(react@19.2.0))(react@19.2.0)
- typescript:
- specifier: ~5.6.2
- version: 5.6.3
-
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diff --git a/src/css/custom.css b/src/css/custom.css
index d0f8f16..2c26cbd 100644
--- a/src/css/custom.css
+++ b/src/css/custom.css
@@ -43,3 +43,26 @@
.footer--dark {
background-color: #000000 !important;
}
+
+/* Mermaid diagram edge labels - adapt to theme */
+:root {
+ --mermaid-edge-label-color: #000000;
+ --mermaid-edge-label-bg: rgba(255, 255, 255, 0.8);
+}
+
+[data-theme='dark'] {
+ --mermaid-edge-label-color: #ffffff;
+ --mermaid-edge-label-bg: rgba(0, 0, 0, 0.8);
+}
+
+/* Apply edge label styles to Mermaid diagrams */
+.mermaid .edgeLabel,
+.mermaid .edgeLabel .label,
+.mermaid .edgeLabel .label span {
+ color: var(--mermaid-edge-label-color) !important;
+ background-color: var(--mermaid-edge-label-bg) !important;
+}
+
+.mermaid .edgeLabel rect {
+ fill: var(--mermaid-edge-label-bg) !important;
+}
diff --git a/static/img/logo.png b/static/img/logo.png
index 1316016..b92edd0 100644
Binary files a/static/img/logo.png and b/static/img/logo.png differ