AI governance evidence for AI Committees and DPOs

Most AI governance programs have a clear process for the approval decision — the AI Committee votes, the DPO signs off, the CISO clears it. What they lack is a structured evidence record to support that decision.

Without a structured record, the AI Committee is approving based on a slide deck or a written description from the team building the system. That is not a defensible governance posture. When an auditor or regulator asks “what did you assess, and how did you decide?”, the answer needs to be a record — not a meeting notes file.

Drel produces a per-system security clearance that serves as the evidence artifact for an AI Committee review. The clearance contains:

• A structured threat model for the specific AI system
• A required controls list with lifecycle gates (before pilot, before production)
• The attack paths through the system, derived from its design, and the controls checked in its code
• Proposed fixes in the Jira ticket, and the check of each merged pull request
• A control gap analysis — what is missing or not yet evidenced
• A decision memo: Approved / Conditional / Restricted pilot / On hold / Declined
• Named re-assessment triggers for when the clearance requires revisiting
• A sign-off record — who reviewed, when, and on what version

The clearance exports as a structured PDF evidence pack suitable for attachment to governance meeting minutes, audit files, or regulatory submissions.

For organizations pursuing ISO 42001 certification, Drel produces evidence for clauses 6 (planning and risk) and 8 (operation and AI system lifecycle). The per-system risk assessment and control plan are the primary artifacts required for the clause 6.1.2–6.1.4 evidence file.

For the EU AI Act, deployers of high-risk AI systems retain obligations under Article 9 (risk management system) and Article 11 (technical documentation). Drel produces the risk management record and control evidence that supports these obligations. It does not perform conformity assessment — that requires a notified body for applicable systems.

Your AppSec lead or security architect runs the review in Drel, in five steps:

1. Model. Drel rebuilds the AI system from its repository and design docs.
2. Threat model. Every attack path, mapped to the frameworks above, with the controls each requires.
3. Attack. The attack paths through the system, from entry point to target, derived from its design; a path whose control is missing is a finding.
4. Fix. Drel proposes the fix in the Jira ticket and checks the merged pull request.
5. Monitor. Drel re-checks the clearance when the code changes, with a gate in your CI; agents can ask for it over MCP.

Then the committee reviews the evidence pack: members comment on individual sections, request changes, and view the control gap list, without needing a Drel account. Configured committee members sign off on the security clearance; the sign-off record is versioned and audit-logged. Named triggers (model change, new tool, scope expansion, the end of the clearance's validity period) fire a re-assessment; a change that adds a model, provider or tool reopens only the parts it affects, and the earlier clearance is preserved as version history.

Drel does not certify systems, attest compliance, or guarantee audit outcomes. It produces the structured evidence record that supports your own governance decision. The clearance decision is yours — Drel provides the analytical foundation for it.

For regulated sectors requiring third-party conformity assessment, that process is separate and outside Drel's scope.