Enables querying corporate knowledge such as HR policies, vendor contracts, and support FAQs, with every answer grounded in an exact source and retrieval quality and hallucination rate explicitly measured.
Enables AI assistants to crawl, index, and retrieve information from technical documentation using semantic search, with optional knowledge graph validation for code hallucination detection.
Creates and searches private, local RAG libraries from documentation to ground AI assistants in authoritative sources, reducing hallucinations by providing current, accurate context from your own docs instead of relying on outdated training data.
Enables traceable, version-aware question answering over product documentation, combining vector and graph retrieval to return cited evidence and support agentic workflows.