Aadhaar N.E.X.U.S

National Equity eXecution & Utilization System

A data-driven planning and early-warning system that measures digital equity, anticipates Aadhaar demand, and simulates where UIDAI should act first.

Overview

Aadhaar N.E.X.U.S is an interactive Streamlit dashboard that provides nationwide visibility into the Digital Equity Index (DEI) across 36 states/UTs and 645+ districts.

🌐 Live Dashboard: 👉 https://aadhaar-nexus.streamlit.app/

Key Features

• State to District Drill-down: Select any state/UT to see district-level performance
• Real-time KPIs: View DEI, Access Health, Update Load, and Stability scores
• Risk Classification: Automatic categorization into Healthy, Access Stress, Update Burden, Stability Risk
• Smart Recommendations: AI-generated suggestions for each district
• Export Reports: Download detailed district reports as text files
• Dark Mode Support: Full compatibility with Streamlit's dark theme

Metrics Explained

Metric	Description	Direction
DEI (Digital Equity Index)	Overall composite score	Higher is better
Access Health Score	Enrollment infrastructure accessibility	Higher is better
Update Load Score	Biometric/demographic update burden	Lower is better
Stability Score	Service delivery consistency	Lower is better

Coverage

Zone	States/UTs	Districts
South	7	148
West	5	115
East	10	188
North	9	188
Total	36	645

Quick Start

# Install dependencies
pip install -r requirements.txt

# Run the dashboard
streamlit run app.py

Project Structure

uidai_dashboard/
  app.py                    # Main Streamlit application
  requirements.txt          # Python dependencies
  README.md                 # This file
  data/
    district_equity_all_india.csv  # Consolidated DEI data

Technology Stack

• Frontend: Streamlit
• Visualization: Plotly
• Data Processing: Pandas
• Styling: Native Streamlit components (Dark Mode compatible)

Deployment

This app is ready for deployment on:

• Streamlit Cloud: Push to GitHub, connect to Streamlit Cloud
• Vercel: See deployment guide in DEPLOY.md
• Heroku: Use Procfile with streamlit run app.py

License

Developed for UIDAI Hackathon 2026