Why it matters
RAG governance decides eligible sources, conflict winners, escalation paths, and audit evidence. Without it, retrieval is probabilistic compliance and security risk.
Exfiltration does not require hacking when filters are loose. Legal discovery needs logs of what bots could retrieve.
Prompt injection and data exfiltration via retrieval are security review topics now. Governance logs are how you prove what was retrievable on the day of an answer, not what you wish had been.
Customer DPAs increasingly ask about automated answers sourced from private documents. RAG governance is part of the compliance narrative.
How it works
Compile retrieval policies per app: collections, states, age limits, verification requirements.
Log filters, suppressed chunks, and policy blocks for debugging and audit.
Align governance changes with access reviews and third-party ingestion approvals.
Provide non-engineer dashboards for legal, support, and compliance stakeholders.
Approve new ingestion connectors through the same review as new collections. Plugins that add sources bypass governance when ingestion is decentralized.
Export denied-retrieval and suppressed-chunk logs for audits quarterly. Audits need machine-readable evidence, not screenshots.
Example
Nintendo chatbot retrieval policy allows only verified, public-safe collections updated within the last review cycle. Internal Nintendo runbooks are invisible to the policy even if a query semantically matches.
When someone asks about enterprise SSO setup, retrieval returns nothing from public collections. Governance routes to a safe fallback: link to sales contact, not an improvised answer from a leaked chunk.
Common mistakes
- 1Governance rules living in spreadsheets while production retrieval ignores them
- 2Filtering only by app ID without checking document lifecycle status
- 3No logging when chunks are excluded, making silent failures invisible
- 4Separate RAG and permissions teams that never align on collection design
- 5Assuming reranking fixes unauthorized retrieval
Definitions are useful. Governed knowledge is better.
Wiki helps you turn these concepts into a real system for the knowledge behind your AI.
See Wiki in action