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Knowledge Assistant — RAG Over Policies, Docs, and Internal Knowledge

Answers grounded in company documents, not model memory

RAG Knowledge Assistant case study preview

THE CHALLENGE

Generic chatbots answer confidently even when the right document was never retrieved. Growing teams need a safer assistant that knows when it has evidence and when it should refuse, ask a follow-up, or route to a person.

OUR APPROACH

We built ingestion, chunking, metadata filters, vector search, citation formatting, conversation re-grounding, and answer checks around the source material. Access and retrieval rules can be tied to teams, roles, or document groups.

THE RESULTS

The assistant gives staff a faster way to find operational knowledge while keeping answers tied to source context. It is built for mid-market teams that need practical internal AI without a six-month enterprise rollout.