Local Search Engine, Built for AI Agents.
We spent months building a complete RAG pipeline. It was technically elegant, but we had to admit: it wasn't good enough. Here are the six root problems we encountered, and how we solved them.
A lightweight Rust CLI tool that connects to the Linkly AI desktop app, enabling you to search, browse, and read local documents from your terminal. It also serves as an MCP bridge for AI agents to access Linkly AI.
A skill pack following the Agent Skills open standard. Once installed, 30+ AI platforms including Claude Code and Codex CLI can directly search, browse, and read your local documents.
Traditional RAG splits documents into chunks and feeds them to AI. We took a different approach: build a structured outline for each document, letting AI browse like a researcher — scan the table of contents, navigate to relevant sections, then read precisely.
Your contracts, reports, papers, and proposals are AI's 'dark matter.' Traditional RAG chops documents into fragments and feeds them to AI — with poor results. We took a different approach: let AI browse your file cabinet like a researcher.
