AI management systems
Model cards, fairness and bias documentation, and judge audit events map to the AIMS controls that ask you to evidence ongoing AI risk management.
AI compliance
Governance frameworks ask you to show that a control ran, on what, and with what result. ZNYX produces those artifacts as a by-product of enforcement, generated per environment from the policy that actually executed.
Model cards, fairness and bias documentation, and judge audit events map to the AIMS controls that ask you to evidence ongoing AI risk management.
Logging, human oversight hooks, accuracy and robustness evidence, and technical documentation for systems placed on the EU market.
Detector scorecards and drift monitoring provide the Measure function; policy versioning and rollout provide Manage.
A per-environment coverage scorecard generated from the detectors your policy actually enables.
Workflow
Pin a policy bundle version per environment so the control you evidence is the control that ran.
Every decision writes an append-only audit event with trace id, detector verdicts, and policy version.
Export the coverage scorecard, detector metrics, and model cards for the period under review.
Hand over artifacts tied to real traffic instead of a questionnaire full of assertions.
ZNYX produces evidence that supports these frameworks. It does not certify you against them, and ZNYX itself does not currently hold SOC 2 or ISO 27001 attestation, those are on the roadmap and are not claimed today. Mapping to specific clauses is provided to accelerate your own assessment, not to replace it.
FAQ
What evidence ZNYX produces, which frameworks it maps to, and where certification stops.
Pull the open-source runtime, drop it into your stack, and start enforcing policy in minutes, free, forever. Add the hosted control plane when you want centralized policies, evidence, traces, and team workflows.