Local Search Engine, Built for AI Agents.
AI multiplies both the value and the risk of your data. Meanwhile, local compute power, the AI agent toolchain, and your own digital assets are all pointing toward the same conclusion: local-first is not a fallback—it's the future.
Claude is smart, but it has no idea what's in your files. Connect your local documents, and what it can do for you changes completely — here are 4 real-world scenarios.
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.
