AI Web Browser
An open-source AI-agentic web browser that turns ephemeral web content into organized, retrievable knowledge using multi-pass RAG reasoning.
The Problem
Web research disappears the moment you close a tab. Bookmarks are graveyards. When you actually need that article about distributed consensus you read three weeks ago, it's gone. Traditional search gets you new results, not your past research.
The Approach
Multi-pass RAG reasoning with confidence scoring (70–95% range). Instead of one retrieval pass, the system iteratively refines its understanding — if confidence is below threshold, it re-queries with reformulated context. Unified vector search (Weaviate) + full-text search (Typesense) for semantic understanding and exact-match precision.
Added Apple OpenELM integration (8 local models, 6 specialized strategies) for privacy-focused local processing. The key design decision: making cloud AI optional — everything can run locally if your data is sensitive.
The Result
Open-source research copilot, MIT licensed. 46 commits, full microservices architecture. Glass morphism UI with drag-and-drop, real-time indexing, and Phoenix AI observability for monitoring LLM performance in production.
My Role
Full-stack, solo. System architecture, RAG pipeline design, React frontend, Weaviate + Typesense integration, local model support, deployment automation.