This project implements a multi-agent AI system that autonomously executes enterprise workflows with minimal human intervention.
The system demonstrates procurement-to-payment automation using intelligent agents that can plan, execute, monitor, and self-correct workflows while maintaining a complete audit trail.
- Autonomous workflow execution
- Multi-agent collaboration
- Failure detection & self-healing
- Real-time workflow monitoring
- Full audit trail (explainable decisions)
- SLA tracking & escalation
- Orchestrator Agent – Manages workflow execution
- Data Agent – Retrieves and validates data
- Decision Agent – Selects best options
- Execution Agent – Performs actions (APIs/mock)
- Verification Agent – Validates completion
- Monitoring Agent – Detects failures & SLA risks
- Request validation
- Vendor selection
- Approval process
- Payment execution
- Verification
- Python
- FastAPI
- SQLite
- React (Vite)
- Tailwind CSS
- Axios
Agentic_AI/
├── backend/
├── frontend/
├── README.md
cd backend
pip install fastapi uvicorn
uvicorn main:app --reload
cd frontend
npm install
npm run dev
POST /start-workflow
{
"item": "Laptop",
"budget": 80000
}
GET /workflow/{id}
- 90% reduction in workflow time
- Significant cost savings
- Reduced manual errors
- Faster decision-making
- Improved SLA compliance
- Procurement-to-Payment
- Employee Onboarding
- Contract Lifecycle Management
- Meeting Intelligence Systems
“We are not just automating tasks — we are automating decision-making.”
- Integration with real enterprise APIs
- Advanced ML-based decision models
- Predictive workflow optimization
- Voice-based interaction