AI Governance & Audit Readiness
When the auditor asks “how do you control your AI?” — you’ll have an answer, with evidence.
We implement the controls, documentation, and evidence needed to support audits and align with frameworks such as NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
When governance readiness is the right fit
Companies selling into regulated industries or enterprise accounts, and any organization with AI in production that expect an audit, a certification initiative, or an upcoming EU AI Act obligation.
- Regulated or enterprise sales
- AI already in production
- Audit or EU AI Act deadline ahead
Where AI governance breaks down
Missing governance documentation
Enterprise customers and regulators asking for AI governance documentation you don't have.
Frameworks without implementation
EU AI Act, ISO/IEC 42001, and NIST AI RMF requirements landing on your desk with no technical implementation behind them.
Policies disconnected from production
Policy documents that exist on paper but aren't backed by actual controls in your systems.
No AI system inventory
AI deployed across the company with no registry of what's running, what data it touches, or who approved it.
Deals stalling in review
Procurement and security reviews stalling deals because your AI story has gaps.
The governance layer we put in place
AI inventory
A model and AI-system registry: everything running, its purpose, its data, and its risk class.
Ownership and approval
Every system in the registry has a named owner — and a record of who approved it running in the first place.
Evaluation gates
Automated quality and safety checks that block bad model changes before they ship.
Logging and evidence
Audit logging across your AI workflows — inputs, outputs, decisions, and human overrides, retained and searchable.
Change control
Drift monitoring wired into your governance reporting, not just your engineering dashboards.
Review-ready evidence
An evidence pack assembled for review: the artifacts, logs, and documentation needed to support an audit.
Framework alignment
Controls and evidence mapped to relevant framework requirements — without presenting the engagement as certification or legal advice.
- NIST AI RMF
- ISO/IEC 42001
- EU AI Act
How the engagement runs
Inventory
We map every AI system, model, and prompt currently running — what it does, what data it touches, and who owns it.
Gap review
We compare what's actually in production against your target framework, and flag where policy documents aren't backed by real controls.
Controls and evidence
We build the logging, eval gates, and drift monitoring your systems are missing, and start capturing the evidence they generate.
Readiness handover
We hand over the framework mapping and an evidence pack assembled for your auditor — the artifacts, logs, and documentation needed to support an audit review.
What you receive
AI system & model registry
A model and AI-system registry: everything running, its purpose, its data, its risk class, its owner.
Audit logging
Audit logging across your AI workflows — inputs, outputs, decisions, and human overrides, retained and searchable.
Evaluation gates
Eval gates: automated quality and safety checks that block bad model changes before they ship.
Governance reporting
Drift monitoring wired into your governance reporting, not just your engineering dashboards.
Framework mapping
Framework mapping to NIST AI RMF, ISO/IEC 42001, and the EU AI Act — implemented controls, not just policy PDFs.
Audit evidence pack
An evidence pack assembled for review: the artifacts, logs, and documentation needed to support an audit.
4–8 weeks
Depending on the number of AI systems and target framework.
$18k–45k depending on scope
Final scope depends on the number of AI systems, identified control gaps, and target frameworks.