An AI-powered platform for national workforce intelligence, designed to identify hidden talent, predict skill gaps, and support data-driven policy decisions.
Overview
The National Talent Intelligence Engine transforms workforce analysis from simple degree counting into behavioral skill intelligence.
Instead of asking:
“What qualification does a person have?”
The system asks:
“What can this person actually do — regardless of degree, location, or digital presence?”
It analyzes 88 behavioral dimensions to build a Skill Genome for individuals and aggregates insights at state and national levels.
Problem Statement
India faces three major workforce challenges:
Hidden talent in rural and low-access regions
Skill mismatch between education and industry demand
Migration of skilled individuals due to lack of local opportunities
Over-reliance on digital signals (GitHub, LinkedIn) that ignore non-digital skills
This platform helps governments, NGOs, and planners:
Discover high-potential individuals
Identify digital divide zones
Predict migration risks
Design targeted skill and infrastructure interventions
Data Foundation
The system uses a high-fidelity synthetic national dataset:
12,500 individual profiles
20 Indian states
65% Rural / 35% Urban distribution
Digital Access levels: High / Limited / Offline
Opportunity Levels: High / Moderate / Low
24-month historical timeline for trend analysis
Dataset inspired by:
PLFS (Periodic Labour Force Survey)
NSSO skill distribution patterns
NSDC sector data
Anti-fraud logic includes anomaly detection using Isolation Forest.
Core Intelligence Architecture
- Behavioral Skill Scoring
Each individual is scored (0–100) across behavioral vectors:
Creation Output (proof of work)
Learning Agility
Offline Capability
Digital Presence
Innovation & Problem Solving
Experience Consistency
Community Collaboration
Economic Activity
- Domain-Specific Intelligence
Scoring logic adapts by sector:
Domain Priority Signals Technology Digital presence, projects, GitHub Agriculture Offline capability, yield performance, field innovation Creative Portfolio output, originality Business Collaboration, economic activity Skilled Trades Experience consistency, offline work
This allows detection of:
Master craftsmen
Farmers with high productivity
Technicians without formal degrees
- Hidden Talent Detection (Key Innovation)
Hidden Talent is identified when:
Skill Score > 70 AND (Rural OR Low Digital Access)
This helps identify:
High-potential individuals without digital footprints
Skilled workers outside formal systems
- Growth & Trend Analysis
The system analyzes learning velocity:
Emerging Skills
Stable Skills
Declining Skills
Obsolescence Risk
Talent Velocity
- National Risk Intelligence
State-level metrics include:
Digital Divide Risk
Skill Deficit
Migration Pressure
Composite Structural Risk:
Risk = 0.4 * Digital Divide + 0.4 * Skill Deficit + 0.2 * Migration Risk
Key Modules Regional Intelligence Map
Interactive heatmap showing:
Hidden Talent Density
Structural Risk Zones
State Specialization
Market Pulse
Demand vs Supply analysis across domains:
Technology
Data & Research
Creative
Business
Skilled Trades
Social Impact
Identifies:
Talent shortages
Surplus sectors
Emerging pipelines
Skill Genome
Individual capability visualization:
Core Strength
Emerging Skills
Declining Skills
Cross-domain synergy
AI-based career transition pathways
Example:
Farmer → Sustainable Agriculture Consultant Manual Tester → QA Automation Engineer
Policy Engine
Automatically generates recommendations:
Expand rural broadband
Launch state skill programs
Create local employment hubs
Promote remote work ecosystems
Alerts System
Real-time intelligence:
Structural risk warnings
Migration alerts
Skill decline signals
Technology Stack
Frontend
React (Vite)
Tailwind CSS
Framer Motion
Recharts
Lucide Icons
Backend
Python Flask
Pandas, NumPy
Scikit-learn
Gradient Boosting
Isolation Forest
Data
Synthetic national census generator
CSV / JSON based processing
Architecture
Monorepo Structure:
project/ │ ├── backend/ │ app.py │ models/ │ data/ │ ├── frontend/ │ src/ │ components/ │ └── README.md
Running Locally Backend cd backend pip install -r requirements.txt python app.py
Runs on:
Frontend cd frontend npm install npm run dev
Runs on:
Deployment
Frontend: Vercel Backend: Render
Monorepo deployment with separate root directories.
Use Cases
Government workforce planning
State skill missions
NGO talent discovery
Rural employment programs
Digital divide assessment
Migration prevention strategies
Impact Vision
The system enables:
Discovery of hidden talent beyond degrees
Inclusion of non-digital workers
Data-driven policy instead of assumptions
Reduction of regional inequality
Smarter national workforce planning
Project Status
Prototype with:
Full-stack implementation
88 behavioral intelligence dimensions
National-level analytics
Real-time dashboards
Future Enhancements
Integration with real government datasets
ML-based demand forecasting
District-level intelligence
Mobile data collection app
Real-time labor market APIs