Edgecase - Supply Chain Analyser for Risk and Overconfidence

A production-ready AI-powered platform for real-time supply chain risk monitoring, disruption detection, and predictive analytics. Edgecase combines advanced data scraping, machine learning, and interactive visualization to help organizations build more resilient supply chains.

Features

Core Capabilities

• Global Trade Route Overview: Interactive map visualization with disruption markers and India domestic mode
• Real-time Dashboard: Live monitoring of supply chain risks, events, and statistics
• 3D Supply Chain Graph: Interactive network visualization with node selection and connection highlighting
• AI-Powered Analysis: NVIDIA NIM integration for high-performance intelligent event processing
• Automated Data Collection: 15+ RSS feeds and 6+ news sources with continuous polling
• Risk Assessment: Multi-factor risk scoring with overconfidence detection
• RAG Query System: Ask questions about your supply chain data using natural language
• Dataset Analysis: Comprehensive analytics on scraped data with visualizations

Data Sources

• News Feeds: Supply Chain Dive, FreightWaves, Reuters, Bloomberg, The Loadstar, Supply Chain Lens
• Weather Data: OpenWeatherMap integration for climate impact analysis
• Trade Restrictions: OFAC sanctions, export controls, tariffs tracking
• Custom Scraping: Auto-crawler for discovering new articles from seed sites

India-Specific Features

• Domestic Mode: Focus on India's supply chain ecosystem
• Major Ports: Mumbai, Chennai, Kolkata, Visakhapatnam, Kandla, Cochin
• Manufacturing Hubs: Bangalore, Pune, Ahmedabad, Delhi NCR, Hyderabad
• India Trade Policies: Specialized tracking of India-specific restrictions

Tech Stack

Backend

• Framework: FastAPI (Python 3.10+)
• Databases:
  • PostgreSQL - Structured data storage
  • Neo4j - Graph database for supply chain networks
  • Qdrant - Vector database for RAG
• AI/ML:
  • NVIDIA NIM - High-performance AI inference
  • Llama 3.1 405b / 4-Maverick 17b models
• Scraping:
  • BeautifulSoup4 - HTML parsing
  • aiohttp - Async HTTP requests
  • feedparser - RSS feed processing

Frontend

• Framework: Next.js 15 with App Router
• Language: TypeScript
• Styling: Tailwind CSS with custom dark theme
• State Management: React Query (TanStack Query)
• Visualization:
  • React Force Graph 3D - Network visualization
  • Custom SVG maps - Geographic visualization
• UI Components: Lucide React icons, custom components

Quick Start

Prerequisites

• Docker & Docker Compose
• Python 3.10+
• Node.js 18+
• NVIDIA API Key (for LLM services)

1. Clone and Setup Environment

git clone <repository-url>
cd Edgecase
cp .env.example .env
# Edit .env with your configuration

2. Start Docker Services

docker-compose up -d

This starts:

• PostgreSQL (port 5432)
• Neo4j (port 7474, 7687)
• Qdrant (port 6333)

3. Backend Setup

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

Backend runs on: http://localhost:8000

4. Frontend Setup

cd frontend
npm install
npm run dev

Frontend runs on: http://localhost:3000

5. Start Ollama (Optional for RAG)

ollama pull qwen2.5:3b
ollama serve

Production Deployment

Ready to deploy? See the complete deployment guide for Vercel + Neon + Render:

• 📖 DEPLOYMENT_GUIDE.md — Step-by-step production setup (Vercel frontend + Neon DB + Render workers)
• ✅ DEPLOYMENT_CHECKLIST.md — Pre-deployment checklist and quick reference

Quick Deploy Summary

Component	Hosting	Setup
Frontend (Next.js)	Vercel	Push to GitHub, auto-deploy
Database (Postgres)	Neon	Free tier, $0-10/month
Workers (Scrapers/Feeds)	Render	$7/month starter plan
Vector DB (Qdrant)	Qdrant Cloud	Free tier (2GB), $20+/month
Graph DB (Neo4j)	Neo4j Aura	Free tier, $15+/month

Total estimated cost: $0-30/month (free tier) to $80+/month (production)

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                      Next.js Frontend (Port 3000)                │
│  Dashboard │ Trade Overview │ 3D Graph │ Events │ RAG Query     │
│  Risk Analysis │ Scraping Control │ Weather │ Restrictions      │
└────────────────────────┬────────────────────────────────────────┘
                         │ REST API
┌────────────────────────▼────────────────────────────────────────┐
│                   FastAPI Backend (Port 8000)                    │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐          │
│  │   Scraping   │  │ Risk Analysis│  │   AI/RAG     │          │
│  │   Engine     │  │   Engine     │  │   Engine     │          │
│  └──────────────┘  └──────────────┘  └──────────────┘          │
│  • RSS Feeds (15+) • Risk Scoring   • NVIDIA NIM API          │
│  • Auto Crawler    • Overconfidence • Vector Search           │
│  • News Scrapers   • Graph Analysis                           │
└────────────────────────┬────────────────────────────────────────┘
                         │
┌─────────────────────────────────────────────────────────────────┐
│                   Data Layer (Docker)                            │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐                       │
│  │PostgreSQL│  │  Neo4j   │  │  Qdrant  │                       │
│  │  :5432   │  │:7474/7687│  │  :6333   │                       │
│  └──────────┘  └──────────┘  └──────────┘                       │
└─────────────────────────────────────────────────────────────────┘

Key Pages

Page	Route	Description
Dashboard	/	Main overview with risk metrics and recent events
Supply Chain Graph	/dashboard/graph	3D network visualization
Events	/dashboard/events	All events with filtering and full article view
Risk Analysis	/dashboard/risks	Comprehensive risk assessment
Dataset Analysis	/dashboard/analyze	Analytics on scraped data
Scraping Control	/dashboard/scraping	Manage data collection
Ask AI	/dashboard/query	RAG-powered Q&A
Weather Impact	/dashboard/weather	Climate-related disruptions
Trade Restrictions	/dashboard/restrictions	Sanctions and export controls
About	/dashboard/about	Project information

Configuration

Environment Variables

Create .env in the backend directory:

# Database
POSTGRES_HOST=localhost
POSTGRES_PORT=5432
POSTGRES_DB=edgecase
POSTGRES_USER=edgecase
POSTGRES_PASSWORD=edgecase123

# Neo4j
NEO4J_URI=bolt://localhost:7687
NEO4J_USER=neo4j
NEO4J_PASSWORD=edgecase123

# NVIDIA API (required)
NVIDIA_API_KEY=your_nvidia_api_key_here

# OpenWeatherMap (optional)
OPENWEATHER_API_KEY=your_api_key_here

RSS Feeds

The system automatically monitors 15 RSS feeds including:

• Supply Chain Dive
• FreightWaves
• Reuters Business/Tech
• Bloomberg Markets
• The Loadstar
• Semiconductor Engineering
• And more...

Usage

Starting Data Collection

1. Navigate to Scraping Control page
2. Click Start Scraping for one-time scraping
3. Or enable Continuous Mode for automated polling
4. RSS feeds auto-start on backend launch (polls every 5 minutes)

Querying with AI

1. Navigate to Ask AI page
2. Type your question about supply chain data
3. AI processes using RAG over scraped content
4. Get intelligent answers with source citations

Development

Backend Development

cd backend
# Install dev dependencies
pip install -r requirements-dev.txt
# Run tests
pytest
# Format code
black .

Frontend Development

cd frontend
# Type checking
npm run type-check
# Linting
npm run lint
# Build for production
npm run build

API Documentation

Once the backend is running, visit:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

Acknowledgments

• Supply chain news sources for data
• Open-source community for amazing tools
• NVIDIA NIM for high-performance AI capabilities

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Version: 1.0.0