What they built

Agentic_Food_Rescue_System

The Problem: Tons of edible food from restaurants go to waste daily because coordinating pickups with local NGOs is logistically difficult, extremely time-sensitive (perishability), and burdened by language barriers in grassroots charity networks. What It Does: Built on NitroStack (an MCP framework), this system uses AI to autonomously rescue surplus food. When a restaurant logs a donation, the system queries a PostgreSQL database to calculate Haversine distances to nearby NGOs, strictly filtering by capacity and perishability constraints. It then triggers an automated, real phone call to the optimal NGO using Twilio. Instead of robotic English, it uses Sarvam AI's Text-to-Speech to speak fluently in the NGO's regional language (e.g., Tamil, Hindi). If accepted, it formally allocates the food, assigns the nearest available gig-worker delivery executive to transport it, and handles end-to-end background SMS communications and JSONB audit logging. Who It Is For: Restaurants & Donors seeking a zero-friction, automated way to prevent food waste and earn CSR metrics. Grassroots NGOs & Community Kitchens who can receive localized phone calls instead of struggling with complex English apps. Delivery Executives looking for optimized, proximity-based gig tasks. What Makes It Special: Agentic Autonomy: Acting via Model Context Protocol (MCP) tools, an LLM orchestrator entirely manages dispatching, retry-logic, and negotiations without human input. Hyper-Local Voice Tech: Integrating Sarvam AI for native-language Twilio voice calls completely removes digital friction for rural or local charity workers. Safety-First Logistics: Hard-coded SQL geospatial constraints ensure perishable (e.g., non-veg) food is only routed within safe micro-radii (5km).