The SVRNOS 7-Layer Model of AI Governance

The SVRNOS 7-Layer Model of AI Governance is part of the SVRNOS governance research published by Sushee Nzeutem (Sovereign OS LLC). It is the architectural locator map that complements the SVRNOS Governance Error Register (GER) classification taxonomy and the Non-Content Safety Attestation (NCSA) evidentiary receipt format: GER names what kind of governance failure occurred, NCSA proves the governance layer ran, and the 7-Layer Model identifies where in the technical stack the failure or control sits. Abstract The SVRNOS 7-Layer Model is a reference architecture that separates AI governance into seven independently failing layers and gives buyers, builders, auditors, and regulators a shared map for locating failures before classifying them. The seven layers (L1 Compute Substrate, L2 Component & Provenance, L3 Routing & Boundary, L4 Evidence Transport, L5 Session & State, L6 Risk Interpretation, L7 Application Enforcement) are inspired by the OSI reference model used in computer networking and adapt the layered-decomposition pattern to a domain that lacks a widely adopted deployment-layer reference map. The contribution of this paper is the seven layers and their boundaries, the dependency ordering rationale (in particular the L5 / L6 ordering), the four-test gate that distinguishes governance roles from build roles, a 2D role-mapping matrix, an inter-layer contracts framing, and the placement of the model within the existing regulatory lineage (ISO 38500, ISO 42001, NIST AI RMF, EU AI Act, AIGN OS, DecisionSpace OS, OECD). The model is companion to the SVRNOS Governance Error Register (GER), which catalogs structural governance failures; the 7-Layer Model assigns each GER code to a layer. Companion publications SVRNOS Governance Error Register (GER) v0.2 — the failure-classification taxonomy (110 codes across the seven layers) Non-Content Safety Attestation (NCSA) v0.2 — the procedural-evidence receipt format that proves a governance layer ran Full methodology, in-progress work, regulatory engagement notes, and contributor acknowledgments at https://svrnos.com/research/svrnos-7-layer-model.