Empowering India’s rural workforce with AI-driven job matching, voice assistance, and Panchayat-verified trust.
KaamSetu bridges the gap between rural workers and local employers through an AI-powered job exchange and community mediation platform.
The app enables daily wage laborers and small contractors to connect, verify, and collaborate — even in low-connectivity rural areas, through offline and SMS-based access.
- Over 80% of India’s rural workforce still depends on word-of-mouth for daily wage jobs.
- Rural unemployment stands at ~7.4% (CMIE, 2024).
- No organized or trusted digital platform exists for rural labor exchange.
- Workers face payment disputes, fraud, and lack of skill recognition.
- Urban-focused job portals exclude rural and semi-skilled workers.
| Type | Description |
|---|---|
| Primary Users (B2C) | Rural and semi-urban daily wage workers: farmers, masons, carpenters, artisans, construction workers (age 18–50). |
| Secondary Users (B2B / Governance) | Local employers (contractors, MSMEs), Panchayats, NGOs for worker verification and dispute mediation. |
- 🤖 AI Skill-Match Engine – Matches jobs based on skills, location & wage preference.
- 📱 Offline + SMS Access – Works seamlessly without internet via Gupshup/Twilio API.
- ✅ Verified Worker Profiles – Panchayat-level digital verification builds community trust.
- 🗣️ AI Voice Assistant – Natural, multilingual interaction for low-literacy users.
- ⚖️ Community Mediation – Local dispute resolution between workers and employers.
- 🌍 Multi-Language Support – Auto-translates job posts and worker profiles.
| Existing Platforms | KaamSetu Advantage |
|---|---|
| Focused on urban, skilled jobs | Built for rural & unorganized workforce |
| Requires full internet | Works offline / via SMS |
| No verification system | Panchayat & community verified |
| Static job listings | AI-driven smart recommendations |
| Layer | Tools / Frameworks | Description |
|---|---|---|
| Frontend | Flutter / React.js | Cross-platform app + web UI (works offline) |
| Backend / APIs | FastAPI (Python) / Node.js | Authentication, data handling, matching |
| Database | Firebase Firestore / PostgreSQL | Stores users, jobs, verification data |
| AI Engine | Python (scikit-learn / TensorFlow Lite) | Skill & location-based matching |
| Messaging Layer | Twilio / Gupshup API | SMS alerts & verification |
| Admin Dashboard | React Admin / Streamlit | Panchayat-level verification & analytics |
| Cloud Hosting | Google Cloud / AWS | Backend & ML model deployment |
| Voice Assistant | Dialogflow / TensorFlow Lite | Multilingual voice commands |
[User App / SMS Interface]
↓
[API Gateway / FastAPI Backend]
↓
[Database + AI Matching Engine]
git clone [https://github.com/](https://github.com/)<your-username>/KaamSetu.git
cd KaamSetu
3. Backend Setup
cd backend
pip install -r requirements.txt
uvicorn main:app --reload
4. Frontend Setup
cd frontend
flutter pub get
flutter run
5. Firebase Configuration
Add your Firebase config file to /frontend/lib/firebase_options.dart
Enable Firestore, Authentication, and Cloud Functions.
6. SMS Integration
Create a Twilio or Gupshup account.
Add credentials in .env:
7. AI Model
Place trained model in /ml_model/kaamsetu_model.pkl
The model runs using TensorFlow Lite or scikit-learn.“Empowering rural livelihoods through AI, accessibility, and trust.”
↓
[Panchayat / Admin Dashboard]