This is Part 3 of a three-part series on AI governance architecture. In Part 1 , we explored the negative proof problem why signed receipts can't prove that unauthorized actions didn't happen. In Part 2 , we examined pre-execution gates that evaluate policy before execution occurs. Today, we'll build a complete reference architecture showing exactly how these components fit together in a production system. Note: This series explores architectural patterns for AI governance based on regulatory requirements and cryptographic best practices. The layered architecture and code examples presented are conceptual frameworks for educational purposes, adaptable across different tech stacks and deployment environments. We've established the conceptual foundation for pre-execution governance: evaluate policy before execution rather than after, create denial proofs that demonstrate prevention rather than just detection, maintain deterministic policy evaluation to enable replay verification.…