Find out exactly where your AI governance will fail an audit —
before an auditor does.
A focused, evidence-based assessment of your AI systems against all 7 stages of the AI Evidence Chain™ — the framework built from 27 years of enterprise AI governance experience, scoped for companies without a compliance department.
What is the AI Evidence Chain™ Audit?
EU AI Act | ISO/IEC 42001 | NIST AI RMF
It's a 4-week gap assessment of your organization's AI governance posture, run against all 7 stages of the registered AI Evidence Chain™ framework. We inventory every AI system in scope — including shadow AI — classify each by EU AI Act risk tier, and map current-state controls against ISO/IEC 42001 requirements and NIST AI RMF functions. The deliverable is a prioritized gap report with a remediation roadmap that names accountable owners for every finding, not a generic checklist you have to interpret yourself.
THE GAP YOU CAN'T SEE
The Problem This Solves
Most companies using AI can't answer a simple question with evidence:
"Show me how this AI system makes decisions, and prove you're monitoring it."
Not because they're negligent — because nobody has ever mapped it. AI tools get adopted by individual teams, vendors quietly ship AI features into existing software, and six months later there's no single person who can say with confidence what AI the business is actually running, let alone document how each system was validated, deployed, or monitored.
This is the gap regulators, auditors, and increasingly customers are starting to test for.
Not intentions.
Not policy documents.
Evidence.
The AI Evidence Chain™ Audit exists to close that gap — fast, and without committing you to a large program before you know if you need one.
THE FRAMEWORK BEHIND THE AUDIT
What the Audit Assesses: The 7 Stages
The AI Evidence Chain™ is RaaSify.AI's proprietary 7-step governance framework — a registered trademark (BOIP Reg. No. 1551399, registered August 25, 2026, held by Ma Cherie Cortez, PhD). It creates a traceable record from business intent through data, build, validation, deployment, monitoring, and incident response. It ensures every AI decision can be defended to regulators, auditors, and boards — replacing policy theatre with operational evidence that lives in delivery workflows, not binders.. The audit evaluates your organization against each stage and tells you, in plain terms, where you're covered and where you're exposed:
AI System Inventory
Is there a documented reason each AI system exists, and who approved it?
Data
What date feeds each system, where did it come from, and is that lawful and appropriate?
Build
How was the system built or configured, and is that process documented?
Validation
Was the system tested for accuracy, biasm and safety before going live — and can you prove it?
Deployment
Who approved go-live, under what conditions, and what guardrails were in place?
Monitoring
Is the system's real-workd behavior actively tracked, or was it "launched and forgotten"?
Incident Response
If the AI system causes a problem tomorrow, is there a defined process — or does everyone improvise?
Most organizations can name a few of these stages after a conversation. Almost none can produce audit-ready evidence for all seven without a structured assessment — that gap between knowing about governance and being able to prove it is precisely what this audit measures.
THE DELIVERABLES
What You Get
IS THIS YOU?
Who This is For
STRONG FIT IF
NOT THE RIGHT START IF
THE EXPERIENCE BEHIND THE FRAMEWORK
Why RaaSify.AI
The AI Evidence Chain™ was built by Ma Cherie Cortez, PhD, drawing on 27 years of global IT leadership and enterprise AI governance work with organizations including Philips, AB InBev, DLL, and Lloyds Banking Group. That experience is now applied specifically to small and mid-sized companies — the same rigor used at global enterprise scale, without the Big 4 price tag or a 6-month engagement timeline.
Frequenty Asked Questions
Most engagements complete within 4 weeks from kickoff, depending on how many AI systems and business units are in scope. You'll get a fixed timeline before starting, not an open-ended estimate.
Not typically. The audit is primarily interview-based and documentation-based — walking through how each AI system is used, approved, and monitored. Deeper technical access is only needed in specific cases, and would be scoped upfront.
That's the point of doing it early. The findings report is prioritized specifically so you know what genuinely needs urgent attention versus what can wait — nothing here is designed to alarm you into a bigger engagement than you need.
No — the assessment maps to EU AI Act risk tiers, ISO/IEC 42001 clauses, and NIST AI RMF functions simultaneously, so the findings are useful regardless of which specific regulation or standard applies to your business or industry.
No. The audit is a standalone, fixed-scope engagement. The findings report includes a recommendation for next steps, but you're free to act on it internally, hire elsewhere, or do nothing further.
Both. AI regulation isn't limited to the EU — Colorado's SB 24-205 and Texas's TRAIGA are already active US state-level AI laws, with more states expected to follow. If your business operates in or sells into the US, the audit's findings are mapped against the relevant state-level obligations alongside the EU AI Act, ISO/IEC 42001, and NIST AI RMF — not just European regulation.
A fixed-scope, evidence-based review — sized for your business.
Built from enterprise governance experience at Philips, AB InBev, DLL, and Lloyds Banking Group. Applied now, entirely, to companies your size.