Agentic RAG
Retrieval pattern where agents plan, retrieve, validate, and synthesize across multiple steps and sources.
What is Agentic RAG?
Agentic RAG replaces the fixed embed-then-generate pipeline with a workflow: a planner decomposes the question, retrievers route per sub-question, a validator checks evidence, and a synthesizer cites. It is the dominant pattern for cross-system enterprise questions that traditional RAG cannot answer reliably. See Agentic RAG vs Traditional RAG.
Why it matters for on-premise & regulated AI
Agentic RAG lets the agent decide what to retrieve, when, and whether to search again — which means retrieval decisions themselves become agent behavior that needs governing. Running agentic RAG privately keeps the query rewrites, intermediate retrievals, and reasoning steps (which often contain more sensitive context than the final answer) inside your boundary and inside a single auditable trace.
Read the full guide: Agentic RAG — in-depth article →
Related terms
Putting Agentic RAG to work?
VDF AI runs governed AI agents on your own infrastructure — on-premises, sovereign cloud, or air-gapped. Book a working session to map the architecture.
Talk to VDF AI