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BUAgents: Enterprise Multi-Agent Operating System

BUAgents is an intelligent business platform designed for modern enterprise full-value-chain operations. It deeply integrates advanced AI technologies including Large Language Models (LLM), General Agents, and Domain Agents to achieve automated collaboration and intelligent decision-making for business processes.


Figure 1. BUAgents Architecture Overview

1. Multi-Agent Driven Autonomous Business System

BUAgents constructs a variety of intelligent agents with clearly defined roles, enabling the platform to perceive, understand, reason, collaborate, and execute across diverse business scenarios. These agents form a Multi-Agent System (MAS) that covers the complete chain from market insights to transaction completion:

  • General Agents handle cross-domain reasoning, task scheduling, and process orchestration;
  • Domain Agents dive deep into specific business scenarios such as Marketing Agents, Sales Agents, and Procurement Agents, delivering high-precision professional decisions;
  • Execution Agents interface with enterprise rules and integrate with ERP, CRM, and other systems to achieve closed-loop task execution.

This multi-agent architecture significantly enhances enterprise operational responsiveness, coordination, and intelligence.

2. Seven Business Data Pools for Dynamic Knowledge Ecosystem

BUAgents builds a "Seven-Pools-in-One" business data structure to capture, model, and semantically enhance critical operational behavior data in real-time:

  1. Market Pool: Captures external information including industry trends, competitor dynamics, and customer demands;
  2. Target Pool: Records enterprise strategic goals and decomposed KPIs;
  3. Information Pool: Aggregates interaction data including customer communications and internal collaborations;
  4. Project Pool: Centralizes project lifecycle data for visualized monitoring and evaluation;
  5. Order Pool: Tracks the complete lifecycle from leads to delivery;
  6. Lost-Order Pool: Analyzes reasons for order attrition to inform strategy optimization;
  7. Partner Pool: Organizes industry partner and supply chain ecosystem data for competitive analysis and strategy formulation.

These seven data pools interconnect and complement each other, enabling agents to reason and make decisions based on dynamic business states.


Figure 2. Shared Market Pool System


Figure 3. Six Core Business Data Pools

3. Three Knowledge Bases for Enterprise Experience Retention

BUAgents establishes a systematic knowledge management framework through three knowledge bases for long-term enterprise knowledge accumulation:

  • Private Knowledge Base: Stores proprietary enterprise knowledge such as policies, procedures, cases, and documents;
  • Interaction Knowledge Base: Records learning data generated from interactions between agents and employees, customers, or suppliers;
  • Public Domain Knowledge Base: Integrates industry knowledge, technical literature, and policy information from public sources.

These three knowledge bases work synergistically to enable BUAgents to continuously improve knowledge reuse rates, achieving "transferable experience, quantifiable capabilities, and explainable decisions."


Figure 4. Knowledge Base Architecture

4. 15 Business Processes Covering Full BU Lifecycle

BUAgents deeply embeds into the full-chain operational management scenarios of Enterprise Business Units (BU), empowering from strategy to execution. It covers:

Brand, Strategy, Marketing, Sales, Procurement, Product, Production, Process, Quality, R&D, Logistics, HR, Administration, Finance, and Legal — 15 business processes in total.

In each process, agents can assist with analysis, provide strategic recommendations, execute tasks, or automate workflows, building a sustainable and evolving intelligent business operation system.

5. BUAgents Value Proposition

  • Automation: Enables autonomous business flow, reducing manual workload;
  • Intelligence: Enhances operational efficiency through multi-agent reasoning and decision-making;
  • Explainability: Increases decision transparency through rules and knowledge bases;
  • Scalability: Supports integration of new agents and knowledge domains based on enterprise needs;
  • Continuous Learning: The platform self-learns and self-optimizes through ongoing business operations.

Live Demo

Trial Access:


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