Introducing the Rasepi Trust Engine

In an era where AI-driven readership has surged, particularly in internal knowledge bases, the Trust Engine emerges as a crucial tool to ensure that AI models retrieve and utilize only trustworthy and contextually appropriate information. As AI systems often pull outdated or irrelevant content, known as ROT (redundant, obsolete, and trivial), this can lead to confident but incorrect outputs—a concern highlighted by many users. The Trust Engine addresses this by evaluating documents based on freshness, ownership, provenance, policy, sensitivity, and context, providing outcomes such as ALLOW, WARN, BLOCK, or ESCALATE, each with a reason and evidence. Rather than scoring documents, it makes decisions to determine if a piece of knowledge is suitable for a specific actor and purpose. This proactive approach filters out unfit sources before they reach AI models, thus preventing misinformation. The system integrates seamlessly with existing tools, maintaining a provenance ledger for compliance and transparency. As the Trust Engine expands its capabilities, it aims to bridge the gap in AI content safety, ensuring that AI assistants can reliably use the knowledge they access.

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