Use Case

Verify AI answers before they become incorrect.

Your search finds relevant sources, not trustworthy ones. Rasepi checks every source found before it enters the prompt. Only what is current, verified, and approved reaches the model.

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Relevance is not reliability

Semantic search is excellent at finding relevant documents. It cannot detect whether a document is outdated, unverified, or was never approved for this purpose. This is exactly where the Trust Gate comes in.

🔐Gating before generation: A check after retrieval. Unreliable sources never reach the prompt.
🎯Context-basedActor, action, and channel are factored into every decision.
📝With conditions: Warnings trigger citation requirements or notices instead of blindly blocking.
📋Fully logged Every decision is recorded in the ledger for debugging and auditing.
🔗Any pipelineWorks with any RAG stack, chatbot, or agent. No proxy.
🤖Also for agents: Agents that take action are subject to stricter rules than those that only read.

A verification step between searching and responding

You don’t change anything about your model. Rasepi doesn’t read prompts and doesn’t sit between you and your model.

1

Your search finds candidates

The retriever works as before and returns, for example, 20 sources.

2

Rasepi checks and filters

filter-sources returns allowed, flagged, and blocked sources, each with a reason.

3

Only verified sources reach the AI

The model responds using trustworthy sources. The decision is recorded in the ledger.

Only feed your AI knowledge you would trust yourself.

We’ll demonstrate the Trust Gate on your own pipeline.

Request a demo