Exec-Connect: Unified AI Agents System

A unified system combining four specialized AI agents (CFO, CMO, COO, CTO) for SME diagnostics and advisory services.

Architecture

The system consists of:

• Backend: FastAPI application with unified routes for all four agents
• Frontend: Next.js application with unified dashboard and agent-specific pages
• Database: PostgreSQL with pgvector extension for RAG capabilities

Project Structure

exec-connect/
├── backend/
│   ├── app/
│   │   ├── agents/          # All four AI agents
│   │   │   ├── cfo_agent.py
│   │   │   ├── cmo_agent.py
│   │   │   ├── coo_agent.py
│   │   │   └── cto_agent.py
│   │   ├── routes/          # Unified API routes
│   │   │   ├── cfo_routes.py
│   │   │   ├── cmo_routes.py
│   │   │   ├── coo_routes.py
│   │   │   ├── cto_routes.py
│   │   │   └── *_chat_routes.py
│   │   ├── schemas/         # Pydantic schemas organized by agent
│   │   │   ├── cfo/
│   │   │   ├── cmo/
│   │   │   ├── coo/
│   │   │   └── cto/
│   │   ├── tools/           # Specialized tools for each agent
│   │   ├── rag/             # Unified RAG vectorstore
│   │   ├── db/              # Unified database models
│   │   └── main.py          # Main FastAPI application
│   ├── alembic/             # Database migrations
│   └── requirements.txt
└── frontend/                # Next.js frontend (to be created)

Setup Instructions

Backend Setup

1. Install dependencies:

   cd backend
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

2. Configure environment: Create a .env file in the backend/ directory. Required for production (e.g. Railway): DATABASE_URL, OPENAI_API_KEY, CORS_ORIGINS. The backend uses the psycopg2 driver (URL scheme postgresql+psycopg2://).

   DATABASE_URL=postgresql+psycopg2://postgres:postgres@localhost:5432/exec_connect
   OPENAI_API_KEY=your_openai_api_key_here
   CORS_ORIGINS=http://localhost:3000,http://localhost:3003
   LLM_MODEL=gpt-5.1
   RAG_ENABLED=true
   RAG_TOP_K=4

3. Set up database:

   # Create database
   createdb exec_connect
   
   # Initialize Alembic (if not already done)
   alembic init alembic
   
   # Run migrations
   alembic upgrade head

4. Run the backend:

   uvicorn app.main:app --reload --port 8000

   API documentation will be available at: http://localhost:8000/docs

API Endpoints

All endpoints are prefixed with /api:

• CFO: /api/cfo/*

  • POST /api/cfo/diagnose - Run financial diagnostic
  • GET /api/cfo/analyses - List analyses
  • POST /api/cfo/chat - Chat with AI-CFO

• CMO: /api/cmo/*

  • POST /api/cmo/diagnose - Run marketing diagnostic
  • GET /api/cmo/analyses - List analyses
  • POST /api/cmo/chat - Chat with AI-CMO

• COO: /api/coo/*

  • POST /api/coo/diagnose - Run operations diagnostic
  • GET /api/coo/analyses - List analyses
  • POST /api/coo/chat - Chat with AI-COO

• CTO: /api/cto/*

  • POST /api/cto/diagnose - Run technology diagnostic
  • GET /api/cto/analyses - List analyses
  • POST /api/cto/chat - Chat with AI-CTO

Next Steps

1. Frontend Setup: The frontend structure needs to be created (Next.js application)
2. Database Migrations: Set up Alembic migrations for all models
3. Testing: Add comprehensive tests for all agents
4. Deployment: Configure for production deployment

Notes

• All four agents share the same database instance
• RAG functionality is unified but uses separate document tables per domain
• Each agent maintains its own analysis and chat message tables
• User authentication is stubbed out and should be implemented