An AI governance consulting company that makes your AI deployments auditable, compliant, and trusted
Boards and regulators are asking hard questions about AI. Your governance framework should answer them before they do.
Redefine is an AI governance consulting company that helps CTOs and CIOs build AI governance structures that work in production, not just on paper. Policy, controls, and monitoring, scoped to your stack.
Most AI programs outrun their controls
AI moves faster than policy. The gap between deployment and governance is where risk lives.
- Models in production with no audit trail and the board cannot verify decisions.
- EU AI Act, SOC 2, and GDPR requirements accumulate with no clear ownership.
- Vendor AI policy reviewed only at contract renewal, not before deployment.
- Incident response for AI failures is improvised, not structured.
- Every model decision logged, versioned, and traceable to a policy owner.
- Regulatory mapping built into the framework before deployment begins.
- Third-party AI vendor review integrated into procurement and onboarding.
- AI incident runbooks defined and tested before an incident occurs.
Pain context · fragmented AI risk review process
Six phases from AI inventory to continuous oversight
Select any phase to see how we scope and deliver that work. Every phase ships a real document or control, not a slide deck.
Every deliverable ships as a document, a control, or a process
No PowerPoint-only engagements. Every phase produces something your team can act on or present to your board.
AI Policy Authoring
Acceptable use, model lifecycle, vendor assessment, and incident response policies written and versioned. Aligned to EU AI Act, ISO/IEC 42001, NIST AI RMF, and your industry regulator.
AI Risk Register
A tiered registry of every AI system in production and in development. Risk scored, owner assigned, review cycle defined.
Regulatory Mapping
Requirements from EU AI Act, GDPR, and sector-specific regulators mapped to your current controls. Gaps identified and prioritized.
Monitoring and Observability
Model drift thresholds, performance alerts, and logging architecture defined. Integrates with your existing observability stack or builds a new one.
Deployment Review Gate
Pre-production checklist for every AI system before it ships. Bias tests, data lineage, explainability thresholds, and incident runbooks verified before go-live.
Board and Executive Reporting
Quarterly AI governance summary packs built for your board and audit committee. What is live, what is at risk, what has been remediated, and what the team is working on next.
Team Enablement
Governance training for engineers, product leads, and executives. Practical workshops, not compliance theater.
Value · AI governance analyst mapping compliance framework
35% improvement in compliance targeting accuracy
Proof · enterprise analytics team reviewing compliance dashboards
Client
Enterprise Apparel and Retail Organization
Multi-division retail and apparel enterprise requiring AI-driven analytics governance for revenue operations.
The problem
Analytics models were producing revenue recovery recommendations with no governance layer. Decisions from predictive systems were applied without audit trail, ownership, or regulatory review. Reporting was fragmented across ERP systems and consumed over 40% of team capacity in manual compilation.
The result
Predictive analytics now operate with a defined governance layer. Recovery and targeting efforts traceable to policy controls.
How the control layer fits your stack
Governance does not require ripping out your infrastructure. It sits across your existing AI toolchain as a policy and monitoring layer.
Most AI governance consultants stay generic and proof-light
The biggest providers in this space produce broad frameworks and leave implementation to your team. Redefine scopes to your stack and stays through execution.
Scoped before work starts
You receive a line-by-line scope document before any engagement begins. No ambiguous retainers. No scope that expands without a written change.
Deliverable-based, not advisory
Every phase ends with a document, control, or process your team owns. Not a presentation summarizing what the team should do.
Matched to your context, not general
Redefine works with CTOs and CIOs at mid-market and enterprise companies deploying AI in production, not with organizations still evaluating whether to use AI.
Proof you can verify
Every engagement references real prior work. Not aggregate statistics. Not anonymized summaries. Specific deliverables from specific types of programs.
Regulatory currency
The EU AI Act enforcement timeline, ISO/IEC 42001 certification pathway, and NIST AI RMF adoption are tracked and factored into every engagement, not mentioned once in a kickoff slide.
The right team size
You work with a senior consultant throughout, not a delivery team you will never see again after the statement of work is signed. The person who scoped the engagement leads it.
Questions before you engage
Internal risk teams understand your business context well. What they often lack is AI-specific governance expertise and regulatory fluency around EU AI Act, ISO/IEC 42001, and NIST AI RMF. We work alongside your risk team, not in place of them, and hand off a framework they can operate independently.
An initial AI inventory and risk tiering sprint takes 2 to 3 weeks. A full policy framework and governance operating model runs 6 to 10 weeks depending on the number of systems in scope. We scope before work starts, so you know the timeline before committing.
Most organizations using any SaaS tool purchased in the last two years are running AI whether they realize it or not. Predictive scoring in customer relationship management systems, automated routing in support platforms, and large language model features in productivity tools all count as AI under most regulatory frameworks. Governance is relevant from the first system, not from the tenth.
Every document and decision log produced in a Redefine engagement is formatted for audit readiness. Version controlled, owner attributed, and dated. We do not produce slide-based outputs that become stale within a quarter. If you are in a regulated industry (financial services, healthcare, insurance), let us know in the brief and we will tailor the documentation format to your specific regulator.
Pricing is scoped to the number of AI systems in scope, your regulatory context, and the phases selected. A focused 2-week AI inventory sprint starts from $8,500. A full governance framework for 10 to 20 systems runs $22,000 to $45,000 depending on complexity. Ongoing monitoring retainers are available post-framework. See full AI consulting pricing.
Who this engagement is for
Not sure where you fall? Tell us your situation and we will be straight with you. No pitch if there is no fit.
Get a scoped AI governance proposal
No commitment. No pitch. Submit your brief and receive a line-by-line scoped proposal within 3 business days.
Brief received
Brief received, we will review your workflow and send a scoped proposal within 3 business days.
Book a call about our AI governance strategy services
30 minutes with our AI governance consulting company. Your AI inventory, your regulatory exposure, and whether there is a fit. No commitment.
