Open controls and evidence for autonomous AI.
Apeiris publishes a machine-readable control model for AI systems that act on their own. 12 verification domains and 654 controls, each stating what it verifies, the evidence it requires, whether it blocks an action, and how it maps to the frameworks you already answer to. Every artifact is signed and free to use under CC BY 4.0.
What is here today is the open knowledge layer. We are building the platform that evaluates real runtime evidence against these controls.
Twelve domains.
Each domain covers one facet of an autonomous action (who acted, under what authority, over what data, with what effect) in its own namespace, with its own evidence model and attestation.
Security
Threats, controls, and detection
Model Assurance
Model trust, evaluation, and drift
Privacy
Consent, purpose, data rights
Compliance
Classification, dossiers, audit
Identity
Agent identity, delegation, revocation
Agentic
Tool use, action scope, orchestration
Ethics
Fairness, remedy, accountability
Resilience
Continuity, fallback, recovery
Finance
Financial governance, approval limits
Authority
Approvals, policy, contracts, intent
Knowledge
Source authority, citation fidelity
Data Governance
Classification, lineage, integrity
Use it.
No account and no API key. Fetch the JSON, verify it against the signed manifest, and build on it.
Builder docs
Fetch, verify, use: the quickstart, core concepts, and how to cite the corpus.
APIAPI & endpoints
Every published JSON endpoint, grouped by purpose, with copy-ready curl examples.
MCPMCP for agents
One read-only, integrity-checked MCP server that lets agents query the whole corpus.
IntegrityVerify every byte
Recompute every artifact hash and check the manifest's Ed25519 signature in your browser.
ExamplesReference & examples
A runnable reference implementation and worked evidence examples.
ReleasesChangelog
Versioned corpus releases, so you can pin to a release and see what changed.