RAG Knowledge Engine
Retrieval pipeline that grounds LLM answers in a versioned, permission-aware knowledge base.
RAGVector DBLLM
Retrieval + answer demo
Problem
Generic RAG returns confident answers from stale or unauthorized documents. For an internal assistant, that is worse than no answer at all.
Approach
Retrieval is permission-aware and version-pinned: every chunk carries an ACL and a document version, and the ranker filters before the model ever sees a passage.
- Hybrid search (dense + lexical) for recall on jargon and code.
- Per-user ACL filtering pushed into the vector query.
- Citations link back to the exact source version used.
Results
- 40% fewer hallucinated citations versus the naive baseline.
- Answers carry verifiable sources, so reviewers trust the output.