Idea Collision Engine
Overview
Full-stack AI-powered idea collision platform that finds unexpected connections between concepts using vector similarity, featuring a Go backend with Qdrant vector database and a modern React frontend.
Background
A complete idea collision system built to discover non-obvious intersections between concepts. The Go backend implements a vector similarity engine using Qdrant for high-performance nearest-neighbor search, with RESTful API endpoints for idea ingestion, collision detection, and result retrieval. The React frontend provides an interactive interface for submitting ideas and exploring collision results with visual relationship mapping. The architecture demonstrates production patterns including structured logging, graceful shutdown, health checks, and containerized deployment. Technical specs: Go backend with Gin framework, Qdrant vector database integration, React frontend with modern tooling, Docker Compose orchestration, and comprehensive API design.
Preview