TRUST, EVIDENCE & METHODOLOGY

Confidence starts
with clear evidence.

A useful explanation says what is known, how it is known, and what still needs to be understood. That is the foundation of our approach to AI transparency.

EVIDENCE HAS CONTEXT

Different sources.
Different meanings.

These categories describe the basis of a statement. They are not a ranking of safety, and they do not replace a scoped professional assessment.

01

Company-declared

Information supplied by the organization. The declaration identifies its owner, scope, and date; it has not automatically been independently checked.

02

Documented

A supporting record is available, such as an architecture document or policy. A document supports a statement within its scope; it does not by itself prove current operation.

03

Independently corroborated

A separate, identified source supports a specific claim. The method, date, and limitations should be visible. Corroboration of one claim does not validate the whole system.

04

Inferred

A conclusion drawn from available information. Its assumptions and uncertainty should be explicit, and it must not be presented as a directly observed fact.

05

Unknown

Information is missing, unclear, or unsupported. Keep that gap visible so a reviewer knows what to ask next.

OBSERVATION IS SCOPED

A technical observation
is a point of evidence.

A configuration record or observed transfer can inform a disclosure. It should include how it was obtained, what it covered, and when it was captured.

It does not establish every possible data path or future behavior. The current demo contains illustrative records, not measurements of real infrastructure.

RESPONSIBLE DISCLOSURE

Make the explanation accountable.

Define the scope.

Name the product, features, systems, and time period covered. Keep exclusions visible.

Show the basis.

Connect important claims to their source and distinguish headquarters from data-processing locations.

Keep it current.

Assign an owner and revisit disclosures when architecture, providers, or policies change.

What participation means

The Agenticert AI Transparency badge links to a public disclosure. It is not an independent safety certification, regulatory approval, audit opinion, or guarantee of privacy, security, or compliance.

Disclosure first.
A clear basis for confidence.

The first step is helping organizations disclose clearly. Certification could be a separate future phase, with its own scope, evidence, and assessment requirements. The current transparency profile and participation badge do not provide certification.

LET’S BUILD WITH CLARITY

Help make AI easier to understand.

We welcome conversations about evidence, disclosure, and responsible implementation.

Talk to us