Grounding Audit Trail

Grounding Audit Trail treats every RAG output as a chain of custody: which source document, which chunk, which rule or prompt produced the answer. Agencies selling into regulated or high-stakes client work (lending, compliance, claims) cannot ship a retrieval system that returns a plausible answer with no traceable origin. The framework separates two concerns: retrieval grounds the explanation in the client's own documents, while a deterministic layer decides the outcome. ai·rete·rag wires a Rete rule engine to retrieval so each verdict links back to the exact rules that fired, producing repeatable decisions rather than probabilistic guesses. For agencies, this converts RAG from a demo feature into a billable assurance deliverable: clients in audit-heavy sectors will pay for traceability, and the same trail shortens dispute cycles when a client challenges an AI-generated recommendation. Build the trail before the client asks for it.