Proposed AI movement
A financial-services AI output attempts to move from draft language toward a customer-facing or reviewer-facing business consequence.
Case Summary
What the proof case demonstrates
This case is designed for buyers who need to understand whether OntoGuard can govern AI-generated financial-services language before it becomes a regulated or customer-facing action.
Decision Authorization
OntoGuard evaluates risk, evidence posture, uncertainty, route maturity, and release-control status before movement.
Withheld or routed before consequence
The case shows how an output can be blocked, escalated, or routed when release conditions are not satisfied.
Strict-six proof surface
Buyer JSON, full-audit JSON, PDFs, decision receipt, and manifest form an offline-verifiable audit credential.
No-bind posture
The proof surface records whether any protected downstream effect formed and what evidence supports that posture.
Route maturity boundary
Production L5 route completeness requires customer integration, real endpoint enforcement, replay evidence, fail-closed behavior, and outcome closure.
Disclaimer: Sanitized proof case. No customer data, no protected implementation details, no production L5 non-bypassability claim.
Buyer Questions Answered
What a diligence reviewer can inspect
Was release evaluated?
The case shows the control point and the decision state before business consequence.
Why was movement withheld or routed?
The proof describes reason codes, evidence posture, uncertainty, and route status in buyer-readable form.
What package can be reviewed offline?
The strict-six structure makes the result inspectable by business, risk, technical, and procurement teams.
What is not claimed?
The public case does not claim customer-specific production endpoint enforcement or production L5 non-bypassability.