AI-Powered Railway Complaint Intelligence System — 3-tier AI pipeline for multilingual complaint classification and prioritization.
// the problem
Indian Railways receives thousands of complaints daily in multiple languages with no automated way to classify severity, route to the right department, or identify systemic issues across regions.
// the solution
Built a 3-tier AI classification pipeline: Tier 1 uses a fine-tuned DistilBERT model for high-confidence local classification. Tier 2 falls back to Google Gemini 2.5 Flash API for complex cases. Tier 3 uses keyword-based offline classification as the final fallback, ensuring 100% uptime.
// architecture
// features
Multilingual complaint submission (Hindi, Marathi, English)
3-tier AI classification pipeline (DistilBERT → Gemini → Keywords)
Real-time admin dashboard with live stats and analytics
KMeans clustering analysis with SVD projections for pattern detection
QR code-based mobile submission for field officers
Role-based access control with Google OAuth
// challenges & learnings
Training DistilBERT on limited multilingual railway complaint data within hackathon timeframe
Designing a graceful fallback system that maintains classification quality across all 3 tiers
Building responsive real-time dashboard with complex data visualizations under time pressure
Check out the code on GitHub or try the live demo.