PromptLedger: A Nine-Layer Pre-Execution Governance Architecture for Enterprise AI Compliance, Auditability, and Human Oversight

A technical paper presenting PromptLedger, a pre-execution AI governance platform for regulated enterprises, and its nine-layer deterministic governance architecture. It argues that the prevailing model of enterprise AI integration places no governance layer between user intent and model execution, so that policy violations can be detected after the fact but not prevented, and that chat logs and API records do not constitute the audit evidence the EU AI Act and model risk management frameworks such as SR 11-7 require. The architecture is described layer by layer: intent capture into a structured representation, deterministic policy evaluation before any model call, authority verification at the interaction level, risk classification with derivative-based behavioral monitoring that detects escalation across a session rather than only within a request, an execution boundary with semantic oversight of the governed request, the model call itself, output validation against policy and intent, a SHA-256 hash-chained immutable audit log, and a structured human escalation gate that holds output pending documented review. It sets out deployment modes, regulatory mapping, and the paper's position within the Vela Protocol framework, and discloses six provisional patent applications filed with the USPTO covering core mechanisms.