Enables AI assistants to crawl, index, and retrieve information from technical documentation using semantic search, with optional knowledge graph validation for code hallucination detection.
Enables version-aware retrieval over the Neutrinos documentation corpus using hybrid BM25/dense search, reranking, and link-graph expansion to answer queries accurately for the user's specific product version.
Enables natural-language retrieval from a self-hosted documentation index, returning cited answers with deep links, and supports private corpora inaccessible on the public internet.
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 teams to capture and distill knowledge from sessions, meetings, and feeds into a searchable, vector-embedded graph, then retrieve or synthesize it conversationally via semantic search and citations.