Most AI Audits Turn Into Fire Drills. Yours Doesn't Have To.
If a regulator, auditor, or board member can't trace your AI decisions end-to-end,
you don't have evidence of governance. You have stories.
The AI Evidence Chain™ gives you a traceable thread from business intent to incident response, so you can
show auditors evidence, not explain intentions.
27+ Years Global IT Leadership | ISO/IEC 42001 Lead Auditor | EU AI Act | NIST AI RMF
CERTIFIED ACROSS AI, CHANGE & TRANSFORMATION
27+ years in enterprise transformation - across AB InBev, Philips, SAP, DLL, and Lloyds Banking Group. Now applied to AI governance, risk and adoption.
27+
Years of Global IT & Transformation
20+
Countries and Markets
100,000+
Enterprise Users in Global Transformation Programs
THE RISK YOU'RE CARRYING
The Hidden Risk in Every AI Program.
Most enterprises are running AI. Few can prove it's governed. Here's where the exposure lives.
No Evidence Chain
Your AI systems run. But when an auditor asks why a decision was made, no one can show the thread from intent to outcome.
Compliance Fire Drills
"We're just experimenting with AI" stops being harmless the moment the EU AI Act applies. Pilots become high-risk deployments overnight.
Vendor Opacity
Weak AI clauses, no assurance on training data or model changes. Without evidence packages in contracts, you own the liability.
THE SOLUTION
Introducing the AI Evidence Chain™
A traceable thread from business intent to incident response — so you can show, not just tell. Auditors and boards don't want theory.
They want hard evidence that AI controls are designed, operated, and overseen.
The name and mark AI Evidence Chain™ are officially registered with BOIP (Reg. No. 1551399, August 25, 2026) under Ma Cherie Cortez, PhD. In practice, that means when you see this name attached to a governance program, you know exactly who built it and who stands behind it — there's a documented, traceable owner, the same principle the framework itself is built to apply to your AI systems.
Non - Negotiable Evidence Artifacts
- AI System Inventory
- Test & Validation Results
- Model Change Log
- Human Oversight Playbook
- Training Data Provenance
- Formal Approvals with Timestamps
- Monitoring KPI Dashboard
- Versioned Decision Logs
Ask vendors for evidence packages + delivery cadence. If they can't provide it — you're inheriting opaque risk.
90-DAY ROADMAP
From Experimentation to Compliant Operations in
90 Days.
You don't need a 300-page program. You need a disciplined roadmap.
Here's what the first 90 days look like.
See the Reality
- Build AI system inventory (GenAI, embedded ML, vendor AI, shadow AI)
- Classify use cases: prohibited/ high-risk / limited / minimal
- Flag high-risk indicators
- Assign named accountable owners per system
Governance Basics
- Approve concise AI policy
- Define approval gates
- Stand up risk assessment workflow
- Define incident reporting
Operational Controls
- Minimum model documentation
- Human oversight rules & escalation
- Vendor due diligence (EU AI Act clauses)
- Audit trail: inputs, outputs, decisions, overrides
WHAT BOARDS ACTUALLY ASK FOR
5 Audit-Ready Artifacts That Do 80% of the Work.
ISO/IEC 42001 done well is operational governance — these artifacts live in delivery, not just in a binder. Executives don't need a 200-page manual. They need to say: show me the evidence.
AI System Inventory
Proof that you know where AI actually lives across your enterprise.
Owner: AI Governance Lead
Reviewed: Monthly
Risk Assessment Template
Standardised template mapping to ISO/IEC 42001 + EU AI Act risk classifications.
Owner: Chief Risk Officer
Reviewed: Quarterly
Model Change Log
Single source of truth for model lifecycle changes linked to formal approvals.
Owner: Head of Data/ML
Reviewed: Monthly
Human Oversight Playbook
Operational guidance for when and how humans intervene in AI decisions.
Owner: AI Governance Lead
Reviewed: Quarterly
KPI Dashboard (performance · safety · compliance)
Board-ready view of model performance, incidents, drift, complaints, and overrides.
Owner: Chief Data & Analytics Officer
Reviewed: Monthly
GOVERNANCE ARCHITECTURE
AI Governance is NOT a Policy Binder.
It's an Executive Decision System.
If you don't make these 3 calls, your AI program will be governed by default - by vendors, regulators, and incident reports.
1) Risk Appetite
Define what is unacceptable before the first model ships. Safety. Discrimination. Regulatory exposure. Brand risk. Write it as thresholds, not slogans.
2) Operating Model
Central AI CoE for high-risk/regulated environments. Federated hub-and-spoke for scaling enterprises. Pick one as primary. Stop pretending you can have neither.
3) Controls Investment
Budget explicitly for monitoring, red teaming, data quality, vendor assurance. If it's unfunded, it will quietly be skipped.
Use a 1-page decision memo: options · tradeoffs · KPIs · exception approvals. If you're an executive, you own these three decisions.
HOW WE WORK
How RaaSify.AI Works With You.
AI Evidence Chain™ Audit
We Assess your current AI portfolio against the full evidence chain and deliver a prioritized gap report with remediation roadmap.
90-Day Governance Sprint
Structured engagement to get your AI governance from zero to audit-ready: inventory, policy, controls. documentation — in 90 days.
AI Governance as a Service (AI GaaS)
Embedded governance support, monitoring, and compliance advisory as your AI program scales. AI Governance as a Service continuously.
ABOUT THE FOUNDER
Led by Someone Who Has Done This at Scale — Not Delegated It to a Team Who Hasn't.
Ma Cherie Cortez, PhD is the founder of RaaSify.AI and creator of the AI Evidence Chain™ framework. 27 years leading global IT delivery and digital transformation across financial services, healthcare, and the manufacturing sector. She didn't study this framework — she built the operational muscle behind it, program by program.
Big 4 firms bring brand names. They also bring rotating junior consultants and whoever's available that week. RaaSify.AI is different: Ma Cherie leads every engagement, start to finish. No handoffs. No learning on your account.
Her insights on ISO/IEC 42001 and EU AI Act compliance have reached 100,000+ transformation leaders on LinkedIn — because they come from someone who's made these calls under real deadlines, not just written about them.
Curious if it's a fit? The free 30-minute Assessment Call puts you directly in front of the person who would lead your engagement — not a proposal from someone else.
EU AI Act | ISO/IEC 42001 | NIST AI RMF | Cultural Change Management | Global IT Leadership | Digital Transformation | Offshore & Nearshore Delivery | AI Compliance Advisory
Stop Hoping Your AI is Compliant.
Know It is.
Book a call. Let's build your AI Evidence Chain™ together.
Frequently Asked Questions (FAQs)
AI Governance & Compliance — Common Questions
GROUP A — Understanding AI Governance
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) — that 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.
Most organizations can name the 7 steps after reading this. Very few can produce audit-ready evidence for even one of them without a structured build — that's exactly what the AI Evidence Chain™ Audit assesses.
ISO/IEC 42001 readiness requires three things beyond documentation: a defined scope with a complete AI system inventory (including shadow AI), a minimum viable AI Management System with lifecycle controls and evidence trails, and closed gaps across six common failure areas — unclear risk acceptance, weak vendor controls, missing change management, and untested incident playbooks. Auditors test how you run AI, not how you talk about it.
The first 30 days of RaaSify.AI's 90-Day Governance Sprint close the two most common gaps we see: shadow AI visibility and unclear risk acceptance.
EU AI Act readiness follows three phases:
- Days 0–30 establish exactly what AI you're actually running — most organizations discover 30–40% more AI systems than expected once shadow AI and vendor features are included.
- Days 31–60 build the governance basics: policy, approval gates, and risk workflow.
- Days 61–90 operationalize controls — model documentation, human oversight, vendor due diligence, and a full audit trail.
This is the exact structure of RaaSify.AI's 90-Day Governance Sprint — built to take you from "we're not sure what we're running" to audit-ready in one quarter.
The five artifacts that do 80% of the audit work are:
- AI System Inventory
- Risk Assessment Template mapped to ISO/IEC 42001 and EU AI Act tiers
- Model Change Log linked to approvals and rollback plans
- Human Oversight Playbook defining escalation paths, and
- KPI Dashboard covering performance, safety, and compliance.
Each needs a named owner and a review cadence — monthly or quarterly.
Knowing these 5 artifacts takes 5 minutes. Building them so they hold up to an actual audit — with the right ownership, evidence trail, and review cadence — is what most 90-Day Governance Sprint engagements are built around.
Not the version enterprises use. Large companies debate centralized councils, federated hub-and-spoke models, or product-line ownership — real questions, but sized for organizations with dozens of AI systems and multiple business units. Most small and mid-sized businesses need something far simpler: one clearly accountable owner, a lightweight approval step before new AI tools go live, and a regular review cadence.
The mistake isn't picking the 'wrong' enterprise model — it's assuming you need enterprise complexity at all. RaaSify.AI's free Assessment Call helps you find the right-sized structure for your actual team, not a framework built for a company ten times your size.
Executives must own three non-delegable decisions:
- Risk appetite — written as thresholds, not slogans, covering safety, discrimination, and regulatory exposure;
- Operating model — choosing a central council or federated guardrails as the primary structure;
- Controls investment — explicitly funding monitoring, red teaming, and vendor assurance. Skip these, and vendors, regulators, and incident reports will make the decisions for you.
If you're not the final decision-maker on these three calls, this is worth forwarding to whoever is. RaaSify.AI's free Assessment Call is often the fastest way to get executive alignment on all three in a single conversation.
"Number of AI models in production" is a vanity metric — it shows nothing about risk reduction. Behavior-changing KPIs include: % of AI systems inventoried, % risk-assessed pre-release, median time-to-approve high-risk use cases, AI incident rate, % of models under active monitoring, and policy exception trends. Track 6–8 metrics with owners and thresholds, reviewed monthly — not 40 metrics no one acts on.
Tracking these 6 KPIs is a spreadsheet exercise. Reviewing them monthly with real accountability — deciding what to stop, pause, or escalate — is where most internal programs quietly stop showing up. That ongoing management rhythm is what Ongoing AI GaaS provides.
Start with the AI Evidence Chain™ Audit if you don't yet know where your gaps are — it's a fast, focused assessment. Choose the 90-Day Governance Sprint if you already know you need to build governance from scratch and have a deadline (audit, certification, or board mandate) driving urgency. Choose Ongoing AI GaaS if you've already built a baseline and need continuous monitoring, policy updates, and accountability without hiring a full internal team.
Not sure which applies to you? That's exactly what the free 30-minute Assessment Call is for — we'll tell you honestly which one fits, even if the answer is "none yet."
Cost depends on your AI system inventory size, current governance maturity, and how many business units are in scope — a single-product startup and a multi-region financial institution have very different scopes. Most engagements fall into one of three tiers: a focused Audit (lowest investment, fastest turnaround), a structured 90-Day Governance Sprint (mid-range, fixed scope), or Ongoing AI GaaS (retainer-based, scales with your AI footprint).
Rather than guessing at your scope from a generic price list, the free Assessment Call gives you an accurate estimate in 30 minutes based on your actual systems — not a one-size-fits-all number.
Yes — RaaSify.AI offers structured AI governance training alongside consulting, because a framework only works if the people using it understand why it exists, not just what to fill in. Training covers the AI Evidence Chain™ methodology, ISO/IEC 42001 fundamentals, EU AI Act risk classification, and how to run the evidence artifacts (inventory, risk assessments, oversight playbooks) day-to-day — tailored to compliance, product, and engineering audiences separately.
If your team needs to operate the governance program after it's built — not just have it handed to you as a binder — training is often paired with the 90-Day Governance Sprint so the knowledge transfers as the artifacts are built, not after.
All three, but not in the same session. Compliance and risk teams need depth on risk classification, evidence requirements, and audit expectations. Product and business owners need to understand approval gates and when their use case triggers review. Engineering and data teams need the practical mechanics of model documentation, change logs, and monitoring — the parts they'll actually be filling in.
RaaSify.AI structures training by audience for exactly this reason. If you're not sure who from your organization should be in the room, that's a quick conversation to have on the free Assessment Call before you commit budget to the wrong group.
You can — and some organizations should, especially if they have in-house risk and compliance depth and time to spare. Where internal builds usually stall: no one has done this specifically for AI before, so risk tiers get misclassified, vendor AI gets missed entirely, and the "policy" gets written without the evidence infrastructure to back it up in a real audit. The framework is publishable; the judgment calls in applying it correctly are not.
If you want to try building it yourselves first, start with the AI System Inventory — it's the one artifact almost every internal team gets wrong on the first pass. The AI Evidence Chain™ Audit exists specifically to catch those gaps before an external auditor does.
Almost never start over. Most organizations we work with already have something — a policy document, a partial inventory, an informal review process. The AI Evidence Chain™ Audit is designed to assess what you have against all 7 stages, keep what's working, and identify exactly where the gaps are — rather than replacing existing work with a generic template.
If you're mid-maturity, the Audit is almost always the right starting point — it tells us (and you) precisely how much of the 90-Day Governance Sprint you actually need, so you're not paying to rebuild what's already solid.
The AI Evidence Chain™ is built to map directly to ISO/IEC 42001 clauses, EU AI Act risk-tier obligations, and NIST AI RMF functions — it's not a standalone framework invented in isolation. It operationalizes what certification bodies and auditors actually test: documented lifecycle controls, evidence trails, named accountability, and continuous improvement — the same substance auditors look for, structured so it's easy to produce on demand.
The framework gets you audit-ready; a certification decision is always made by an accredited certification body, not by RaaSify.AI. The 90-Day Governance Sprint is scoped specifically to prepare you for that external audit with evidence in hand, not just a policy binder.
No pitch, no deck. We review your current AI landscape together, identify your top 3 compliance gaps in real time, and tell you honestly which service (or none) makes sense — including if the answer is "you're further along than you think and don't need us yet." Most calls end with a clear next step, whether that's booking an engagement or a specific action you can take internally first.
If that sounds useful, the Book a Call section on this page takes 60 seconds to schedule — no obligation attached to filling it out.
Every engagement — starting with the Assessment Call — is treated as confidential by default. Discussing your AI inventory, vendor relationships, or risk exposure with an outside advisor requires trust, and RaaSify.AI does not reference client-specific details, systems, or findings publicly or with other clients under any circumstance. Formal NDAs are standard practice before any deeper engagement (Audit, Sprint, or AI GaaS) begins.
If confidentiality terms are a condition of even having the initial conversation, raise it at the start of the Assessment Call — it's a normal request, not an unusual one.
By the time enforcement deadlines arrive, the AI systems already in production are the hardest to fix — retrofitting governance onto live, high-risk systems is slower and more expensive than building it in from the start. Waiting also means shadow AI and vendor AI features keep expanding unchecked, so the eventual inventory and remediation effort grows every quarter you delay.
The 90-Day Governance Sprint exists because 90 days is a realistic window to get ahead of enforcement — but that window gets tighter, not wider, the longer it's postponed.
What Users Are Saying
Real user feedback shows how a recognized voice in AI governance, read by compliance and transformation leaders across 15+ countries.
Thomas Schubert
Supply Chain Compliance & AI Governance
Jameel Ahmed Siddiqui
AI Governance Researcher & Systems Architect
Rarkimm Fields
Legislative Intelligence + Diagnostic Architecture