The GRACE (Governed Release Architecture for Critical Environments) protocol establishes a six‑layer governance matrix that embeds stability and safety checks directly into the release pipeline of frontier AI systems. Each layer functions as a progressive safeguard: (1) Invariant Extraction – spectral diagnostics of symbolic outputs; (2) Perturbation Stress‑Testing – controlled stochastic probes to reveal hidden fragility; (3) Collapse Detection – monitoring rigidity and entropy trajectories; (4) Governance Triggering – automatic flags that halt unsafe releases; (5) Domain Calibration – tailoring thresholds for medicine, finance, law, and cybersecurity; and (6) Sovereign Oversight – enabling regulators and critical institutions to enforce mandatory release criteria. This architecture is revolutionary because it transforms safety from voluntary guidelines into enforceable structural checkpoints, ensuring that models cannot bypass stability verification before entering sensitive environments. Its impact is profound for sectors such as healthcare, where diagnostic AI must remain structurally coherent; economics and finance, where transaction streams cannot collapse into noise; legal systems, where symbolic codes must resist brittleness; and cybersecurity and sovereign agencies, where resilience against collapse is a matter of national security. The project is led by independent researcher Mohamed Samir Abd Elrahman Selim in Cairo, Egypt, and has advanced from conceptual design to published open‑access frameworks demonstrating feasibility for integration into AI governance pipelines. Documentation and validation are openly archived at [https://doi.org/10.5281/zenodo.19256386] and [https://doi.org/10.17605/OSF.IO/296KP], with author identity verified via [https://orcid.org/0009-0001-2930-3609] and citation record available on [https://scholar.google.com/citations?user=IrKSLv0AAAAJ].
