Pre-Inference Governance

Pre-inference governance rests on a simple asymmetry: what a model never receives cannot appear in what it produces. Controls placed after generation — output scanning, response filtering, post-hoc review — inspect a result that has already been formed from whatever was supplied, and their reliability depends on recognizing every problematic formulation a model might generate, which is an open-ended obligation. Controls placed before invocation operate on a closed set: the records eligible for retrieval, the instructions eligible to load, the identity making the request. Each is enumerable and testable in advance. The practical consequence is that assurance becomes a statement about inputs, which can be demonstrated, instead of a statement about outputs, which can only be sampled.

Centralpoint enforces at both boundaries but weights the first. Classification, redaction and tagging run as records are transformed for indexing, so the embedding layer only ever receives approved material. Governance-tier skills load ahead of any retrieved content and cannot be overridden by it. By the time a model is called, the surface has been bounded, the rules are resident, and the identity has been resolved — the model is being asked a question that was already made safe to ask.