Enables AI assistants to search and query PDF documents through a local RAG system with vector embeddings. Provides semantic document search capabilities while keeping all data stored locally without external dependencies.
Enables AI assistants to interact with local documents (PDF, Markdown, TXT) through tools for discovery, reading, extraction, summarization, comparison, keyword extraction, search, and analysis, ensuring privacy and offline capability.
Enables coding agents to verify verbatim quotes against a local corpus of scientific PDFs, returning exact matches with page locators or typed refusals without using an LLM.
Enables AI assistants to search, read, and retrieve context from local knowledge bases with full-text search, absolute paths, and section-level details.
Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.
