Grabit is a real-time, AI-driven marketplace designed to combat urban food waste. By connecting restaurants with surplus inventory to local consumers at deeply discounted prices, we transform potential waste into affordable, high-quality meals.
- Theme: Social Good & Sustainability
- Core Mission: To eliminate urban food waste through "last-mile" sales and data-driven inventory management.
- The Problem: Overproduction leads to financial loss for businesses and an environmental crisis (methane emissions), while budget-conscious consumers struggle to access quality nutrition.
Grabit moves beyond simple API wrappers to a multi-layered automated pipeline.
- Frontend: Angular – A seamless, reactive dashboard for both Restaurants (to post inventory) and Users (to manage preferences).
- Backend: PostgreSQL on GCP (Cloud SQL) – Optimized for storing complex user-to-cuisine mapping and historical waste logs.
- Agentic AI Pipeline: Developed in Google Colab & VS Code.
Instead of using GenAI as a "chatbot," Grabit utilizes it as a Structural Parser:
- Data Extraction: The AI parses unstructured restaurant "shouts" (e.g., "Got 5 veg plates left, 50% off until 10pm").
- Entity Identification: It identifies the "What, How Much, and When," passing structured data to our custom backend.
- Smart-Matching Engine: Custom Python logic performs a "Pref-Join" between real-time AI entities and the PostgreSQL user-base.
- Push System: Users don't search for food; the food (via AI matching) finds them based on their pre-set "Food DNA" (Cuisine + Restaurant preferences).
- Real-Time Notifications: Automated alerts triggered by the matching engine.
- Waste Visualization: A dedicated suite showing restaurants their "Total Loss Occurred," forcing a data-driven realization of their environmental footprint.
- Lean Manufacturing Integration: Using data to help restaurants adjust their supply chain to prevent loss before it happens.
- Carbon Reduction: Lowering the daily CO2 footprint of participating local businesses.
- Nutrition Accessibility: Providing high-protein meals to students and low-income users at 40-70% discounts.
- Operational Strategy: Shifting the industry from reactive disposal to proactive inventory management.
- Predictive Waste Analytics: Moving from reactive to proactive by analyzing "Loss Occurred" trends to provide Demand Forecasting reports.
- Dynamic Pricing Engine: An automated "Price-Decay" algorithm where discounts increase (e.g., 40% → 70%) as the pickup deadline approaches.
- In-App Booking: Integrated payment gateways to allow users to "Claim" their meal instantly, removing availability uncertainty.