A comprehensive, multi-tenant business intelligence platform designed for modern organizations. This system provides secure data isolation, advanced analytics, AI-powered insights, and role-based access control for enterprise supply chain management and business intelligence.
SupplyWise AI is a production-ready, enterprise-grade platform that combines:
- 🏢 Multi-Tenant Architecture - Complete data isolation between organizations
- 🔐 Role-Based Access Control (RBAC) - Granular permissions and user management
- 📊 Advanced Analytics - Real-time dashboards with interactive visualizations
- 🤖 AI-Powered Insights - Natural language query agent and machine learning
- 🔄 Automated Data Pipelines - ETL workflows with Apache Airflow
- 📱 Modern Web Interface - Responsive Next.js frontend with TypeScript
- Next.js 15 with TypeScript and React 19
- Tailwind CSS for modern, responsive design
- Recharts for advanced data visualizations
- Radix UI and Headless UI for accessible components
- NextAuth.js for authentication
- Zustand for state management
- Framer Motion for animations
- Django 5.1 with Django REST Framework
- PostgreSQL for relational data storage
- MongoDB for document storage and raw data ingestion
- Apache Airflow for workflow orchestration
- MinIO for object storage
- Ollama for AI/ML capabilities
- Docker & Docker Compose for containerization
- NGINX reverse proxy support
- Redis for caching and sessions
- Multi-environment configuration support
- Multi-tenant data isolation - Organizations cannot access each other's data
- Hierarchical role system - Admin, Owner, CEO, Managers, Employees, Clients
- Object-level permissions - Fine-grained access control
- Audit logging - Complete activity tracking
- Secure API endpoints - JWT-based authentication
- Real-time dashboards - Interactive charts and KPI widgets
- Modular analytics - Drag-and-drop dashboard builder
- Data grid system - Dynamic table views with filtering/sorting
- Custom visualizations - Bar, line, pie charts with real data
- Export capabilities - CSV, Excel data export
- Natural language queries - Ask questions about your data in plain English
- Query agent - Intelligent SQL generation from natural language
- Demand forecasting - Machine learning predictions
- Anomaly detection - Automated insights and alerts
- Automated ingestion - Watch folders for new CSV files
- Data transformation - Clean and normalize data with Airflow DAGs
- Schema mapping - Flexible data structure handling
- Real-time processing - Event-driven data updates
- Organization management - Create and manage multiple organizations
- Role-based invitations - Secure user onboarding workflow
- Team collaboration - Share dashboards and insights
- User activity tracking - Monitor platform usage
- Docker & Docker Compose
- Git
- Clone the repository
git clone https://github.com/vcovelli/supply-chain-dashboard.git
cd supply-chain-dashboard- Set up environment
# Copy environment template
cp .env.example .env
# Edit environment variables
nano .env- Start the platform
# Build and start all services
docker compose up -d --build
# Wait for services to initialize (2-3 minutes)
docker compose logs -f- Initialize test data
# Install testing dependencies
pip install -r requirements-testing.txt
# Run unified test suite for complete setup
python unified_test_suite.py --full-setup- Access the platform
- Frontend: http://localhost:3000
- Backend API: http://localhost:8000
- Airflow: http://localhost:8080
- MinIO Console: http://localhost:9001
For comprehensive testing options and troubleshooting, see TESTING_GUIDE.md
| Role | Password | Capabilities | |
|---|---|---|---|
owner@test.com |
Owner | testpass123 |
Full organization management |
manager@test.com |
Manager | testpass123 |
User invites, analytics |
employee@test.com |
Employee | testpass123 |
Analytics access |
admin@supplywise.ai |
Platform Admin | admin123 |
Multi-org access |
- Executive Dashboard - High-level KPIs and organizational metrics
- Operations Dashboard - Real-time operational data and alerts
- Custom Analytics - Build personalized dashboards with drag-and-drop
- Data Grids - Interactive tables with advanced filtering and sorting
- File Upload System - CSV, Excel file processing with schema mapping
- Data Grid Interface - View and manage uploaded datasets
- Schema Validation - Automatic data type detection and validation
- Data Transformation - Clean and normalize data automatically
- Natural Language Interface - Ask questions in plain English
- SQL Generation - Automatic query generation from natural language
- Context Awareness - Understands your data structure and relationships
- Interactive Results - Visualize query results automatically
- Organization Settings - Configure org-level preferences
- User Management - Invite, manage, and assign roles to team members
- Role Configuration - Flexible permission system
- Audit Logs - Track all platform activities
graph LR
A[CSV Upload] --> B[MongoDB Storage]
B --> C[Airflow Processing]
C --> D[PostgreSQL]
D --> E[Django API]
E --> F[Next.js Frontend]
F --> G[Interactive Dashboards]
H[AI Query Agent] --> D
I[Real-time Updates] --> F
- Data Ingestion - Upload CSV files or connect data sources
- Raw Storage - Store unprocessed data in MongoDB
- Transformation - Airflow DAGs clean and normalize data
- Structured Storage - Processed data stored in PostgreSQL
- API Layer - Django REST API serves data with proper permissions
- Visualization - Next.js frontend renders interactive dashboards
- AI Enhancement - Query agent provides natural language interface
- Install dependencies
# Backend dependencies
cd backend
pip install -r backend-requirements.txt
# Frontend dependencies
cd ../frontend
npm install- Database setup
# Run migrations
python manage.py migrate
# Create superuser
python manage.py createsuperuser- Start development servers
# Backend (Django)
python manage.py runserver
# Frontend (Next.js)
npm run dev| Script | Purpose |
|---|---|
./scripts/linux/local/setup.sh |
Complete local environment setup |
./scripts/linux/local/start.sh |
Start all services locally |
./scripts/linux/local/stop.sh |
Stop all services |
docker compose logs -f [service] |
View service logs |
Key configuration options:
# Database Configuration
APP_DB_NAME=supplywise_db
APP_DB_USER=supplywise_user
APP_DB_PASSWORD=your_secure_password
# Django Settings
DJANGO_SECRET_KEY=your_secret_key
DJANGO_DEBUG=False
ALLOWED_HOSTS=localhost,127.0.0.1
# MinIO (Object Storage)
MINIO_ROOT_USER=minioadmin
MINIO_ROOT_PASSWORD=minioadmin
# AI Configuration
OLLAMA_HOST=http://ai:11434- Branding: Update
frontend/public/assets - Styling: Modify
frontend/tailwind.config.js - API Extensions: Add new Django apps to
backend/ - Data Models: Extend existing models in respective apps
# Production build
docker compose -f docker-compose.prod.yml up -d
# SSL/TLS with Let's Encrypt
docker compose -f docker-compose.ssl.yml up -d# Deploy to Kubernetes
kubectl apply -f k8s/- Health Checks: Built-in health endpoints for all services
- Logging: Centralized logging with Docker logs
- Metrics: Prometheus-compatible metrics available
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
- Follow PEP 8 for Python code
- Use TypeScript for all frontend code
- Write tests for new features
- Update documentation for API changes
- Multi-tenant RBAC system
- Advanced analytics dashboard
- AI-powered query agent
- Automated data pipelines
- Modern web interface
- Mobile responsive optimizations
- Advanced ML forecasting models
- Real-time collaboration features
- Advanced Integrations - ERP, CRM, and third-party connectors
- Mobile Application - Native iOS/Android apps
- Advanced AI - Predictive analytics and automated insights
- Enterprise Features - SSO, advanced compliance, custom branding
This project is licensed under the MIT License - see the LICENSE file for details.
- Documentation: /docs folder contains detailed guides
- Issues: Report bugs and request features via GitHub Issues
- Email: support@supplywise.ai
Built with ❤️ for modern enterprises seeking intelligent business insights.