RAG-based enterprise knowledge platform
Historical documents and process data turned into a queryable knowledge base for internal AI assistants — with controlled access.
Documents and process data accumulated over years were effectively un-searchable. The goal: a knowledge base that internal AI assistants can answer from reliably and with controlled access.
Structured historical documents and process data into a queryable form.
RAG (retrieval-augmented generation) pipeline as the foundation for internal AI assistants.
Access control over the knowledge base so answers are bound to permissions.
Governance over sources and answers for traceable results.
- queryquestion to the assistant
- permissionspermission check
- retrieveknowledge base (RAG)
- answeranswer with sources
- audit-logsources & access
denyNo permission, no answer — knowledge stays bound to access rights.
Answers come only from approved sources: the permission check sits before retrieval, and governance covers sources and answers.
A platform that enables enterprise-wide AI queries grounded in reliable knowledge — with governance controls over access to that knowledge.
StackRAG · Vector search · LLM assistants · Access control · Governance
A similar use case?
Tell us about your initiative — we'll show what an auditable path there looks like.
SIFAMO GmbH — Berlin · Frankfurt