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Find Out If Your AI Is Actually Ready for Production
Review data handling, access controls, and audit trail against the frameworks your compliance team use, and identify what's missing before an incident does.
A working AI pilot isn't automatically ready for production
AI pilots often reach production before anyone has documented what data they touch, who approved their access, or what happens when something goes wrong. This is what a real AI readiness assessment exists to catch: we review what's actually in place against what your compliance team, auditors, or applicable regulations require, so you know what needs to be addressed before scaling.
A clear picture of what AI is already running in your organization, sanctioned or not, the shadow AI discovery and detection work that most access-control reviews skip, what data it touches, and who has access to it.
An assessment of your current policies, approval trails, and documentation against what NIST AI RMF, ISO 42001, and applicable regulations such as the EU AI Act's risk classification tiers require, including whether the system has a retained evaluation set, a named owner for ground truth, a documented passing threshold, and a regression process that runs automatically when the underlying model version changes. Without that, a system that's "working" today has no defensible way to prove it's still working after the next silent provider update.
A direct look at where access controls, data handling, or human-override points are missing, or exist but were never written down.
What needs to change before the system is defensible, ranked by the risk each gap carries and the effort required to address it.
Whether personal data is detected and redacted before reaching a model, and whether the system's data is processed and stored somewhere your regulatory obligations actually permit, including SBP requirements for Pakistani financial data and SDAIA/PDPL for Saudi-touching systems. Silence on either is a gap, not a clean result.
What the review actually tells you
At the end of the review, each system is classified based on the gaps we find and what they mean for scaling.
Ready to Scale
At the end of the review, each system is classified based on the gaps we find and what they mean for scaling.
Needs Remediation First
The system works, but one or more gaps need to be addressed before it is ready to scale. We identify exactly what's missing and give you a realistic timeline for closing each gap.
Not Ready
The gap is large enough that scaling now would be a real risk. You get a clear explanation of the risks involved and what would need to change before scaling makes sense.
See what our customers say
From review to a documented, defensible system
A structured engagement that turns an unreviewed AI system into one your compliance team can actually stand behind.
Inventory What's Running
We map every AI system in scope, including the shadow AI nobody's inventoried yet, what it touches, who approved it, and what's already documented versus what only exists as institutional knowledge.
Review Against the Frameworks
We check current policies, access controls, and audit trails against NIST AI RMF, ISO 42001, and the regulations applicable to your industry and use case.
Identify the Gaps
We identify what's missing, whether that's a policy, access control, human-override point, or another control, and rank each gap by the risk it carries.
Build the Remediation Plan
We hand over a prioritized list of what needs to close before this is defensible, with a realistic timeline for each item.
Document & Handoff
The automation goes live with monitoring in place, and we hand over the documentation and access your team needs to operate and extend it.
How we handle data governance and compliance
Data Residency
Your data stays inside boundaries you define, whether that's a zero-retention API, an isolated environment, or on-premises infrastructure, depending on what your governance requires.
Access Control
Every system connection only reaches the data and actions your team has explicitly approved. Nothing is granted by default.
Audit Trail
Every data movement is logged and traceable, so if something goes wrong, your team can see exactly what happened and where.
Rollback & Recovery
A defined rollback path exists before any pipeline goes live, so a bad deployment doesn't become a data incident.
Data Residency & Support Commitments
We state plainly where your data can be processed under your regulatory obligations, and what support tier and response commitment applies once a system is reviewed and live.
The checks every review covers
Every review assesses your systems against key governance, security, and compliance benchmarks to ensure production readiness.
Frequently asked questions
What is an AI governance and readiness review?
How do you find AI tools we don't already know are running?
What counts as a "high-risk" AI system under the EU AI Act?
Do you certify us as compliant with NIST AI RMF or ISO 42001?
How is this different from AI Strategy & Discovery?
How is this different from a formal AI compliance audit?
What if the review finds serious gaps?
How long does a review take?
Who owns the report and the remediation plan?
Do you need full access to review a system?
Can you help close the gaps you find, or just identify them?
What happens after the review
Data & System Integration
Build reliable data and infrastructure with scalable pipelines, cloud systems, and integrations.
Workflow Automation
Catch the exceptions manual work misses, and route only the real ones to a person.
Is your AI actually ready to scale?
Walk us through what's already live, and find out exactly what stands between where it is and where it needs to be.
