Public technical-evidence concepts mapped to the named primary framework sources.
How to read the mapping
Direct implementation support means the cited technical mechanism can produce a named kind of evidence. Partial mapping means it can contribute but cannot discharge the wider obligation or objective.
Every mapping is bounded by the deployment, version, test conditions, evidence retention, and organisational controls around it.
Limit: The mappings do not determine whether an organisation or AI system satisfies a framework.
Limits
What this record does not establish.
Boundary
A mapping is not certification, conformity assessment, readiness scoring, legal advice, or complete coverage.
Boundary
Organisational, legal, lifecycle, retention, and deployment responsibilities remain outside a runtime gate.
Boundary
NIST states that AI RMF 1.0 is under revision; this record maps the named 1.0 edition and must be re-reviewed when a successor is published.
Sources
Versioned references.
Regulation (EU) 2024/1689 primary-authority · Official Journal text, 2024/1689 · verified 2026-09-27 Open source ↗
NIST AI Risk Management Framework 1.0 primary-authority · AI RMF 1.0; NIST revision underway as of 2026-09-27 · verified 2026-09-27 Open source ↗
Implementing the UK's AI regulatory principles primary-authority · Initial guidance for regulators, 6 February 2024 · verified 2026-10-06 Open source ↗
Singapore Model AI Governance Framework for Agentic AI primary-authority · Updated framework, 20 May 2026 · verified 2026-10-06 Open source ↗
OWASP Top 10 for Agentic Applications 2026 primary-authority · 2026 edition · verified 2026-09-27 Open source ↗
The evidence and demonstrations shown here do not run a live engine, reviewer service, executor, or backend, and do not establish a supported integration contract.