Multi-agent, policy-driven AI system for processing sensitive enterprise documents with extraction, analysis, verification, deterministic orchestration, and full audit logging. Designed for regulated environments (banking, finance, insurance).

MoralStack is a governance and safety layer for LLM applications. It analyzes user requests before generation, evaluates risk and intent, and decides whether the AI should answer normally, answer safely, or refuse. The goal is to make AI systems more auditable, controllable, and reliable in sensitive or regulated contexts.

Curated list of AI/LLM tools, papers, and repos for regulated industries -- finance, healthcare, legal.

Compliance-aware LLM workflow for regulated financial environments: policy enforcement, model routing, output validation, and correlated audit trail via LangGraph and OTel.

Declarative form validation library for React with YAML/JSON configs. Ships with BFSI, healthcare & government ID presets (PAN, Aadhaar, IFSC, GST). Audit-ready, i18n-supported, and runtime-customizable. Build compliance-ready forms without reinventing validation logic.

Policy-bounded decision traces for AI-assisted financial operations: versioned policy enforcement, human-in-the-loop gating, cost attribution, and auditable case outcomes.

Python and SQL data analysis of cosmetic products, ingredient patterns, and chemical risk indicators built on a relational SQLite database.

A governance framework for Retrieval-Augmented Generation (RAG) systems in regulated industries. Provides citation tracking, audit trails, human-in-the-loop validation, and compliance patterns.

AI/LLM security testing library mapped to OWASP LLM Top 10 2025 and MITRE ATLAS. 191 payloads organized by domain with CI/CD integration for regulated industries.

A (relatively) comprehensive exhaustive resource detailing the gray area surrounding the already ambiguous nature of the statutes ruling regulated markets.