Become independently verifiable
GAFAIG certification verifies whether AI governance processes and meaningful human oversight are implemented, operational, and producing real oversight outcomes.
Certification is evidence-based, scope-defined, and published as a public trust record only when the verified outcome meets GAFAIG requirements. Private evidence, reviewer materials, and internal workflows remain protected.
GAFAIG verifies governance execution, not governance claims
Frameworks describe how AI governance should operate. GAFAIG verifies whether those governance processes are actually implemented, operational, and producing real oversight outcomes in practice.
An organization may have policies, internal controls, responsible AI statements, or governance documentation, but external stakeholders cannot independently verify whether those processes are functioning.
GAFAIG publishes a certified public trust record backed by signed proof, lifecycle status, verification endpoints, and portable trust surfaces.
What GAFAIG evaluates
Certification focuses on the real-world operation of governance processes across the AI system lifecycle. The review is scoped, evidence-based, and tied to a specific organization, system, program, or governance boundary.
Accountability structures, oversight roles, escalation paths, decision authority, and governance ownership.
Documented AI system purpose, deployment context, affected parties, data use, and human decision points.
Evidence of evaluation, monitoring, testing, risk assessment, performance review, and oversight checks.
Mitigation actions, incident response, lifecycle controls, renewal readiness, and continuous governance operation.
From application to public proof
GAFAIG certification follows a structured lifecycle that separates private review from public trust publication.
The organization identifies the AI system, governance program, or certification boundary to be reviewed.
GAFAIG reviews governance materials, oversight processes, controls, monitoring evidence, and related operational records.
A certification outcome is determined through the GAFAIG verification process. Certification logic is not computed in the UI.
If certified, the outcome is published as a public trust record with signed proof and verification surfaces.
Certification status may change based on renewal outcomes, new information, incidents, or governance changes.
Certified records may renew, expire, suspend, or revoke according to GAFAIG lifecycle and policy rules.
Certification creates a public trust record, not public exposure of private evidence
GAFAIG is designed so organizations can prove certified AI governance without exposing internal systems, reviewer materials, raw evidence, scoring details, or private workflow records.
Evidence, findings, reviewer materials, internal workflow, and supporting governance records remain controlled inside the verification process.
The public layer exposes the certification outcome, registry record, lifecycle state, signed proof, and verification surfaces.
Certification outcomes are independently verifiable
A certified GAFAIG record can be verified through the registry, verify page, API, SDK, widget, badge, and modal surfaces.
Standards guide the review; verification proves the outcome
GAFAIG certification assessments may reference published standards, disclosure thresholds, certification policies, and governance requirements.
Start the GAFAIG certification process
Organizations seeking certification should begin by defining the certification scope and reviewing the applicable standards, policies, and certification pathway.