RAGGuard

RAGGuard is an AI + web app that sits between your retrieval-augmented generation (RAG) pipeline and your users, scoring every answer for “groundedness” and forcing verifiable citations. It ingests your knowledge sources (docs, wikis, PDFs, ticket threads), builds a retrieval index, and then evaluates each model response against the retrieved passages. If an answer can’t be supported, it blocks the response, asks for clarification, or rewrites with only supported claims. Teams get dashboards showing top failure topics, missing-document hotspots, and “citation coverage” over time. This is not a magic truth machine: it won’t prove facts outside your corpus, and it won’t fix bad source content. But it will drastically reduce confident nonsense in internal copilots and customer-facing chatbots, and it gives engineering and compliance teams concrete metrics instead of vibes.