I will audit your rag pipeline and fix retrieval accuracy and permissions

Is your RAG app returning the wrong chunks, missing obvious answers, or showing people documents they should not see?

I audit retrieval pipelines and tell you exactly where they break. Chunking that splits tables and headings apart, embeddings that do not match your domain language, no reranking so the best chunk sits at position nine, and permission filters applied after retrieval instead of inside the query.

WHAT YOU GET

A written report of what is wrong, ranked by impact

Specific fixes with the reasoning, not generic advice

Retrieval quality measured before and after

Permission scoping checked against real user roles

I built a permission-aware RAG platform over a large enterprise knowledge base: tenant and ACL scoping applied inside the retrieval query so unauthorized text never enters the prompt, hybrid search with reranking, structure-aware chunking, and traceability to document, section and page.

rag audit

rag pipeline

vector search

llm integration

Send me your stack and a few queries that return bad answers. I will tell you what is likely wrong before you order.

Message me before ordering so I can confirm scope.