CookMyCart

Overview

CookMyCart is an AI-assisted grocery shopping application that helps users decide what to cook based on the items already in their cart. By combining ingredient matching with AI-powered ranking, the platform recommends recipes that maximize ingredient overlap and suggests additional products to complete meals. The system is designed as a modern full-stack web application that demonstrates how AI can enhance grocery discovery and meal planning through intelligent recommendations.

The Problem

Many people buy groceries without a clear plan for what they will cook. Recipe sites require manual searching, and grocery platforms rarely help users connect the ingredients they already have with meals they can actually make. This leads to food waste, inefficient shopping, and a fragmented user experience between meal planning and grocery purchasing.

The Solution

CookMyCart analyzes the ingredients in a user's cart and automatically recommends recipes that can be prepared with those items or with minimal additional purchases. The platform combines deterministic ingredient coverage scoring with AI-based ranking to surface the most practical and appealing meal suggestions, turning grocery shopping into an intelligent meal planning experience.

Core Capabilities

• Ingredient-based recipe recommendations generated directly from the items in a user's grocery cart
• Deterministic ingredient coverage scoring to identify recipes that maximize use of existing cart items
• AI-powered ranking using Vertex AI to improve recommendation relevance and meal discovery
• Product catalog browsing with search and category filtering
• Authenticated user carts with persistent shopping sessions
• Recommendation snapshots and preference persistence for personalized shopping workflows

Technical Overview

CookMyCart is built as a modern full-stack web application using Next.js and React for the frontend and FastAPI with Python for the backend. PostgreSQL provides persistence for product catalogs, carts, recipes, and user preferences. The backend exposes APIs for catalog search, cart management, and recipe recommendations, while Vertex AI is used to enhance recommendation ranking and AI-assisted features. The architecture separates frontend, backend, and background worker services for scalability and clean system boundaries.