The 20-Layer Y.I.N. Mazari Architecture: Completing the Privacy-Preserving AI Governance Stack Through Independent Verification and Cross-Platform Computational Determinism

This paper presents the completed Y.I.N. Mazari Architecture in its final 20-layer form, addressing two compounding failures in AI governance: the verification paradox where organizations cannot prove compliance without trusting their own infrastructure, and the platform determinism gap where AI inference produces different results across hardware architectures. The architecture integrates five physics foundation layers establishing energy-anchored provenance through Landauer limit accounting, domain routing, measurement precision, blockchain anchoring, and deterministic parity verification using Residue Number System arithmetic. Core governance layers enforce constitutional constraints through cryptographic authorization, differential privacy, and multi-party verification. Advanced layers provide zero-knowledge proofs, immutable audit trails, automated regulatory reporting, quantum resistance, and meta-governance oversight. Layer 0E, the Deterministic Parity Engine introduced in this final architecture, achieves bit-exact cross-platform computational reproducibility, enabling independent verification of AI operations by any party on any hardware. Combined with Layer 14, SENTINEL independent verification, the architecture produces governance evidence that no party can forge, no party can suppress, and any party can reproduce independently on arbitrary hardware. The complete 20-layer stack addresses GDPR Article 5, DORA Article 28, EU AI Act Article 50, HIPAA Security Rule, and provides 30-year quantum-resistant durability through NIST FIPS 203 post-quantum cryptography. Patent portfolio: 27 USPTO applications covering the architecture, priority November 23, 2025. The name Y.I.N. honors Yanis, Ilyan, and Neylia Mazari, representing the principle: Your Information Never leaves your control.