Qriton

A checkable record with the answer.

High-accountability AI has to be able to account for itself. On an audit-enabled Qriton KB deployment, answered and refused chats receive tamper-evident receipts. Accepted operations in the managed correction workflow receive their own records.

Traceability, made practical

Qriton KB attaches a checkable receipt to the answer and its cited evidence. Teams can review what was returned and whether the service record is intact. It supports a broader governance programme; it is not a legal certificate or a guarantee that an answer is correct.

Built for accountable teams

Whether a use case is high-risk is a customer and legal determination. The product supplies a useful record for teams that need to explain AI-assisted work.

Safety-related work

Keep the supporting sources, answer, and review history together when the output contributes to a safety-sensitive workflow.

Regulated decisions

Give reviewers a clear trail around AI-assisted work in regulated or high-accountability contexts.

Use the record to support your own review, controls, and evidence programme.

What you can check

The receipt sits with the answer and cited evidence, subject to the deployment's access policy.

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Checkable receipt default

The service records the answer and its supporting evidence in a tamper-evident form that authorized users can verify later.

What a certificate isn't

It lets an authorized verifier check whether this exact exchange matches the deployment's tamper-evident audit log. The log is not independently anchored, and the check is not a guarantee that the answer is correct or a substitute for the rest of a compliance programme.

Questions before you rely on it

Does using Qriton KB make us AI-Act compliant?
No, and be wary of any vendor who says otherwise. Compliance is a full programme: risk management, human oversight, conformity assessment where it applies, and more. A certificate addresses one specific duty: the traceability Article 12 asks for. That's a real piece of the work, not the whole of it.
Is a hash chain literally what Article 12 requires?
Article 12 requires logging that enables traceability and post-market monitoring, but it does not mandate a technology. Our chain is designed to support that goal and adds tamper-evidence. Whether it satisfies your specific obligations is a question for your counsel, not for marketing copy.
What if we're not sure our system is classified high-risk?
Article 6 sets a two-part test, and it is genuinely not always obvious. That's a determination for your legal team. The audit trail is useful either way, because it's the same traceability your auditors and your own risk function want, classification or not.
Does the certificate cover facts we edit or correct?
Accepted correction and removal operations in the managed workflow receive audit receipts alongside the chat records. The proposal, review decision, application, and live release are distinct stages; the receipt is not presented as one atomic, content-bound proof of all four. An active correction can be removed without retraining; retained audit history follows the customer's retention policy.
Can we show a certificate to an actual regulator or auditor?
An authorized user can verify a receipt against that deployment's audit log at /verify. This is a server-side integrity check, not an independently anchored proof. Receipt access on a confidential deployment is yours to control. Whether it satisfies a specific audit is between you and that auditor; we don't represent it as pre-approved by any regulator.
Where does our data go?
Qriton KB supports fully local deployment. External model providers are optional and explicitly configured. This public demo uses the OpenAI integration for answer generation; do not submit confidential information. Answer generation can instead use a local open-weight model such as Qwen, or extractive mode with no generative model. Whole-deployment locality also requires local connectors, embeddings, verification and other configured model roles, plus network controls that enforce the boundary.

Ask it something you'd have to defend.

Use a non-confidential question in the public OpenAI integration demo, then inspect the receipt. Confidential deployments control receipt access.