Verification & Certification
Certification marks and trust registries
A registry entry carries both a badge a person can read and a code an agent can query.
The badge is for the user reading a product page; the mark is for their agent, which checks the registry before relying on a tool. Both resolve to the same record, so neither can drift from the other.
Nutrition labels for AI tools and datasets
A fixed label states the same required fields for every tool, extended for the higher-risk domains.
A higher-risk decision-support tool, such as a debt calculator, shows the same five fields plus a sector extension: the tested error rate against reference cases, known failure modes, the population the test data covers, and the date of the last independent check. That is the standard’s documentation, not this low-risk label’s — so the label links out rather than reproducing it.
‘Accuracy claim’ and ‘last updated’ are the two fields most often left vague. The label makes both explicit and checkable.
Software bills of materials for user-facing tools
The badge recomputes as the tool's components change, so it reflects current supply-chain risk rather than the state on approval day.
The signal covers the supply chain only: the components and their known vulnerabilities. Whether the tool’s method is sound is a separate question, answered by accuracy testing.
Risk-proportionate review of civic tools
Review burden scales with consequence, so an informational tool clears automated checks and a decision-support tool goes to a human.
- Automated checks
Disclosure label complete · no undeclared data collection · passed in 4 minutes
- Human reviewNot required
Not required for informational tools
- Listed
Live in the registry with its label and mark
Every check above links to the published criterion it applies. You can read exactly what will be reviewed before you submit, and if your tool is rejected, you’ll be told which criterion it failed.
Review checks behavior against the stated policies. It does not test whether the outputs are true. That is accuracy testing, a separate duty for decision-support tools.
Lifecycle certification for tools that advise users
A tool's obligations are set by what it claims to do and the consequence of getting it wrong, not by whether it contains AI.
What is the tool’s intended purpose?
Your answer sets the certification tier. Whether the tool uses AI does not matter.
Select the tool’s role to see its tier.
Higher tiers keep their obligations after approval. Monitoring on live use continues after launch.
From voluntary framework to certifiable standard
A tiered self-assessment turns a tool's coverage of a risk-management framework into the certification level the framework itself leaves undefined.
The framework names the discipline; the tiers make it enforceable. A readiness check that maps to a public pass/fail line is auditable. One that maps to nothing cannot be checked.
Grounding and source attribution in AI outputs
Every factual claim in the answer is retrieved from a named source rather than generated, and cited where it appears.
The figures are retrieved from the record, never generated. If a claim can’t be cited, it isn’t stated. The same source information travels with the answer as machine-readable data.
Lightweight certification for the long tail
The lowest tier asks a developer to self-declare, with no third-party gate, so a solo team can clear it in a weekend.
Certify your tool
Two questions about consequence set your tier. Most community tools finish at Tier 1.
Answer both questions to see the tier your tool routes to.
A scheme only the well-funded can complete certifies the largest vendors and shuts out everyone else. Tier 1 keeps the community tools people rely on inside the system, visible and labeled.
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