What is AI compliance evidence?

AI compliance evidence is the set of records and artifacts a compliance, risk, security or audit team uses to assess an AI system or action. Originary makes selected runtime actions and decisions portable and independently verifiable, while stating what the supplied evidence does not establish.

Is Originary an AI governance platform?

No. Governance and control platforms define, apply or manage policies and workflows. Originary prepares and verifies evidence from the systems that observed an action so that another party can review the same set of records.

Does Originary make an AI system compliant?

No. Originary does not interpret laws, certify systems or determine that a requirement has been satisfied. It can support a compliance assessment by providing verifiable records and explicit evidence limitations.

Does this replace logs, observability or a SIEM?

No. Logs and telemetry remain essential for operating and debugging systems. Originary selects and packages the records another party needs to verify outside the source environment.

AI compliance

Signed evidence for AI audits and compliance reviews.

Record important automated actions as they happen so reviewers have something more useful than screenshots and reconstructed timelines.

See an evidence case Start a pilot

Supports evidence collection and review. It does not determine whether a legal, regulatory or contractual requirement is satisfied.

Evidence caseillustrative

3 of 7 elements established. 1 linked, 2 not supplied or not established, 1 complete with limitations.

Gateway decision: signature verified
Tool invocation: signature verified
Result content: digest matches
Payment-provider artifact: linked
Approval record: not supplied
Delivery: not established
Verification report: complete with limitations

The evidence gap

A review needs evidence that outlives the systems that produced it.

When an AI action is reviewed or investigated, the evidence is usually spread across agent runtimes, gateways, approval systems, observability tools, payment providers and internal databases, each with its own identifiers, retention rules and operator-controlled logs. Originary packages the relevant records into one case that another party can inspect, verify and keep.

From runtime to review

How records get from the systems that acted to the people who review them.

Keep your agent framework, AI gateway, observability stack, SIEM, GRC system and approval workflows. Originary collects signed records from them and assembles a case a reviewer can check.

01 Collect
Select only the records and native artifacts relevant to the reviewed action. Private logs remain in the systems that produced them.
02 Verify
Check signatures, record structure, bound digests, issuer information and the supplied verification-key or expected-issuer policy.
03 Assess
Show what the evidence establishes, what is missing, where sources conflict and which properties were not evaluated.
04 Hand off
Export the signed records, linked native artifacts, verification report and timeline so another party can inspect the same case.

Framework support

Records that support evidence work for the EU AI Act, ISO/IEC 42001 and NIST AI RMF.

Originary does not certify an AI system, interpret the law or determine that a control has been satisfied. It gives operators and reviewers portable, verifiable records that can support their own assessment.

EU AI Act

Support selected traceability, record-keeping and technical-documentation workflows with verifiable records of runtime events, decisions and oversight artifacts. Originary does not determine whether a system is high-risk or whether an obligation is satisfied.

ISO/IEC 42001

Support operational evidence for an AI management system, including selected controls, approvals, decisions, changes and reviews. The PEAC mapping is informative and is not certification.

NIST AI RMF

Preserve records that can support selected Govern, Map, Measure and Manage activities. Originary does not replace your AI risk-management process.

NIST AI Risk Management Framework (opens in a new tab)

Framework applicability, evidence sufficiency and legal conclusions remain the responsibility of the organization and its qualified advisers, assessors or auditors.

Review workflows

For the AI actions someone will later have to explain.

Internal audit and control review: Give reviewers the records for selected controls and actions without opening up your operational logs.
High-risk agent-action review: Connect the proposed action, approval or denial, execution record and reported result.
Incident investigation: Preserve the gateway decision, tool or API action, relevant artifacts and verification outcome for a later investigation.
Customer or counterparty assurance: Hand another organization records it can inspect locally under an explicit issuer-and-key policy.
Paid tool or API dispute: Connect authorization, service invocation, result commitment and native payment artifacts while stating whether delivery was actually observed.
Provisioning and access review: Verify reported account, credential, resource, deployment or subscription changes after the originating system is unavailable or inaccessible.

How it fits

How an evidence case fits next to logs and GRC tools.

Question	Internal logs	Governance or GRC system	Originary evidence case
Primary job	Operate and debug a system	Manage policies, controls and review workflows	Hand off verifiable evidence for one case
Verified outside the source system	Depends on the system	Depends on the platform and export	Yes, under an explicit issuer-and-key policy
Requires private-system access	Depends on the system	Depends on the platform	No, for the selected supplied records
Shows missing or conflicting evidence	Depends on the system	Depends on the platform	Explicitly
Replaces existing infrastructure	No	May be a primary workflow system	No, composes with both
Portability	Vendor or system specific	Varies	Open, documented record format

Originary complements your controls and systems. It does not decide which actions to permit, enforce policies or replace the process that determines compliance.

What verification means

A valid signature establishes three things and leaves the rest to you.

It tells you the record is intact and was signed by the key you supplied. Whether the record is complete, and whether to trust the issuer, are still your questions.

ResultSignature valid

CheckedThe supplied key validates the signature.
CheckedThe protected record has not changed since it was signed.
CheckedEvaluated content matches what the record binds.

Not checkedWhether every relevant event was recorded.
Not checkedWhether the issuer, or each statement, should be trusted.
Not checkedWhether an external event or legal requirement was satisfied.

Questions

Common questions about AI compliance evidence.

What is AI compliance evidence?: AI compliance evidence is the set of records and artifacts a compliance, risk, security or audit team uses to assess an AI system or action. Originary makes selected runtime actions and decisions portable and independently verifiable, while stating what the supplied evidence does not establish.
Is Originary an AI governance platform?: No. Governance and control platforms define, apply or manage policies and workflows. Originary prepares and verifies evidence from the systems that observed an action so that another party can review the same set of records.
Does Originary make an AI system compliant?: No. Originary does not interpret laws, certify systems or determine that a requirement has been satisfied. It can support a compliance assessment by providing verifiable records and explicit evidence limitations.
Does this replace logs, observability or a SIEM?: No. Logs and telemetry remain essential for operating and debugging systems. Originary selects and packages the records another party needs to verify outside the source environment.

Start with one action

Start with one consequential AI workflow.

Bring one agent action, gateway decision, approval, paid tool or API call, incident, or provisioning change. We will identify what your systems can honestly record, what a separate reviewer can verify and what evidence would remain missing.

Start a pilot Verify a sample