AI Supply Chain Risk Manager
Live Application: 👉 https://your-app-name.streamlit.app
An AI-driven supply chain monitoring system that detects operational risks, predicts disruptions, and recommends mitigation strategies in real time.
This project simulates an AI Supply Chain Control Tower that continuously analyzes logistics data and provides decision intelligence.
- Real-time supply chain monitoring
- AI risk detection engine
- Supply chain disruption prediction
- Supplier recommendation system
- Global logistics visualization
- Supply chain crisis simulator
- Interactive analytics dashboard
The system behaves like a Supply Chain Monitoring Agent that:
- Observes operational data (orders, suppliers, inventory)
- Analyzes supply chain health
- Predicts disruptions using ML
- Recommends mitigation strategies
Database (PostgreSQL / Supabase)
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AI Monitoring Engine (Python)
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Risk Detection + Prediction
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Decision Recommendation
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Streamlit Control Tower Dashboard
| Layer | Technology |
|---|---|
| Dashboard | Streamlit |
| Backend | Python |
| Database | PostgreSQL (Supabase) |
| Visualization | Plotly |
| Machine Learning | Scikit-learn |
| Data Processing | Pandas / NumPy |
| Deployment | Streamlit Cloud |
The dashboard provides:
• Risk Index Monitoring • Supplier Performance Analytics • AI Decision Explanation • Supply Chain Activity Feed • Logistics Network Visualization • Crisis Simulation Engine
Visualizes logistics operations across multiple cities.
Users can simulate disruptions such as:
• Port shutdown • Supplier bankruptcy • Transportation strikes • Natural disasters
The AI estimates their impact on global supply chain risk.
(Add screenshots here)
Clone the repository
git clone https://github.com/yourusername/AI-Supply-Chain-Risk-Manager.git
cd AI-Supply-Chain-Risk-Manager
Install dependencies
pip install -r requirements.txt
Run the dashboard
streamlit run dashboard.py
PostgreSQL database structure includes:
• Orders • Suppliers • Inventory • Risk Alerts • Recommendations • Order Locations
• Manufacturing supply chains • E-commerce logistics • Global trade monitoring • Smart supply chain control towers
• Reinforcement learning supply chain optimization • Integration with real logistics APIs • Autonomous supplier switching agent • IoT shipment tracking