RAG & Knowledge Systems
Answers your people can verify: production RAG that grounds every response in your own documents and cites its sources, the kind of system I have shipped for the United Nations.
Leaders whose teams lose hours searching documents, tickets and policies, and who cannot roll out AI answers nobody can verify
Institutional knowledge is scattered across systems, finding an answer depends on knowing who to ask, and unverifiable AI responses erode the trust adoption depends on
Your organization's knowledge becomes answerable: cited responses people verify and trust, with relevance you measure instead of hope for
A RAG system your organization can trust: every answer grounded in your documents and cited to its source, with an evaluation harness that measures relevance, from ingestion and retrieval through cloud-native deployment
A working view of the architecture this engagement ships and how it runs in production.
Approach
- 01IngestConnect sources, chunk, embed, and index with lineage
- 02Retrieve & GroundHybrid search and reranking, with every answer required to cite its source
- 03Evaluate & ShipRelevance evals, latency budgets, and production hardening
Ship RAG & Knowledge Systems
30 minutes to map the problem, the data and the fastest path from prototype to governed operation.