42 enterprise AI programs assessed · FinTech, healthcare, and manufacturing
AI governance and risk services that surface every AI risk before your next audit forces the issue
Ungoverned AI is a liability your legal team cannot quantify and your compliance team cannot defend. Our ai governance and risk services give you a complete risk register, a gap analysis across six governance domains, and a remediation roadmap, delivered in weeks, not quarters.
Governance domains
6
assessed end-to-end
governance domains assessed end-to-end
Policy, Risk, Data, Compliance, Models, Incident Response
Most enterprise AI runs on assumptions, not controls
The gap between deploying AI and governing it is where regulatory penalties, reputational damage, and operational failures live. See what that gap looks like and what closing it actually changes.
No central AI inventory
Teams adopt AI tools independently. No one knows how many models are running or what data they touch.
Accountability gaps
No named owner for AI policy decisions. When something goes wrong, responsibility is unclear.
Compliance learns at audit time
Compliance teams discover AI deployments during reviews, not before. Every finding is reactive.
Outputs go unmonitored
Model drift, bias, and hallucination events accumulate without detection or documented response.
No incident response plan
When an AI system fails publicly, there is no documented escalation path, no communications protocol, no rollback process.
Legal cannot answer regulators
Basic questions about what AI you operate and what it does with customer data have no documented answer.
Pain · Security analyst reviewing AI risk documentation
Replace with: analyst at desk marking up printed risk report, focused, desk lamp as key light, slight overhead angle · 1600×520
A complete governance framework built for enterprise AI governance and risk assessment at scale.
Six integrated domains that take your AI program from scattered pilots to governed, auditable infrastructure.
AI Policy and Standards
Enterprise-wide policy architecture covering acceptable use, prohibited applications, ethical review gates, and accountability chains for every AI deployment.
- Use-case policy templates for 12 enterprise functions
- Role-based accountability matrix for each deployment tier
- Ethical review criteria aligned to your risk appetite
Risk Assessment and Tiering
Structured risk classification across all active and planned AI systems: consequence mapping, likelihood scoring, and deployment-gate thresholds before any model reaches production.
- Risk registry with live scoring across all active systems
- Five-tier classification from experimental to mission-critical
- Deployment gates with sign-off conditions per tier
AI Risk Registry — Live View
3 systems flagged for review before next deployment cycle
Data Governance for AI
Training data lineage, access controls, bias detection protocols, and retention schedules that satisfy both your legal team and your model operations team.
- Full lineage tracking from raw data source to model output
- Bias detection tests embedded in the data pipeline
- Role-gated access to sensitive training datasets
Regulatory and Compliance Alignment
Continuous mapping of your AI portfolio against evolving regulations including the European Union Artificial Intelligence Act, General Data Protection Regulation, and sector-specific frameworks in financial services and healthcare.
- Compliance gap analysis against current regulatory frameworks
- Automated alerts when regulatory guidance changes
- Audit-ready documentation packages per deployment
Model Lifecycle — Deployment Pipeline
Development
Bias checks, lineage recorded
Risk Review
Tier classification, gate sign-off
Staging Validation
Performance, drift, fairness
Production
Monitoring, alerting live
Model Lifecycle Management
Structured checkpoints from experimentation through retirement: version control, performance benchmarking, drift monitoring, and deprecation protocols that keep your model estate healthy.
- Four-stage gate process from development to production
- Automated drift detection with retraining triggers
- Version registry with rollback capability at every stage
Incident Response and Escalation
Predefined playbooks for when your AI systems behave unexpectedly: severity classification, stakeholder escalation trees, remediation tracks, and post-incident review processes.
- Three-tier severity matrix with defined response timelines
- Named escalation contacts from technical to executive tier
- Mandatory post-incident review for every Severity 1 or 2 event
How ready is your AI program today?
Work through the 12-point readiness check below. Your score shows which governance domains need attention before your next deployment.
Domain 01: Policy and Standards
Domain 02: Risk Assessment
Domain 03: Data Governance
Domain 04: Regulatory Compliance
Domain 05: Model Lifecycle
Domain 06: Incident Response
Four technical pillars that make governance operational at scale.
Policy without infrastructure is a document. These four components turn your governance framework into a system that enforces itself.
0
controls automated
Automated Control Layer
Policy rules enforced in code, not spreadsheets. Deployment gates, access controls, and retention rules run without manual intervention.
0
model signals monitored
Observability Pipeline
Real-time performance, fairness, and drift signals streamed into a central dashboard. Every anomaly logged, timestamped, and routed to the right owner.
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model versions tracked
Model Registry and Versioning
Every model version, training run, and configuration change catalogued with full metadata. One-click rollback to any prior state in under two minutes.
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audit reports generated
Audit Reporting Engine
Regulatory-ready audit packages generated on demand. Covers decision logs, training data lineage, risk assessments, and incident history in a single structured export.
Governance Framework Flow
Intake
Use-case submission
Risk Gate
Classify and approve
Build
Governed development
Validation
Staged review and sign-off
Production
Monitoring and alerting
Audit
Continuous reporting
A regulated FinTech firm governed 34 AI systems in 11 weeks.
From a spreadsheet-based risk log and zero policy documentation to a fully auditable governance program ahead of their Series B due diligence.
Case Study
The Problem
A Series A FinTech with 34 active AI systems had no formal risk classifications, no policy documentation, and no audit trail. Their investors flagged this as a Series B blocker six months before their target raise date.
Our Approach
We ran a two-week discovery to classify all 34 systems, then built their six-domain governance program in parallel tracks. Policy, risk registry, data lineage, compliance mapping, and incident playbooks all landed inside 11 weeks.
The Outcome
- Series B due diligence passed with no AI governance flags
- 34 systems classified, 11 escalated for immediate remediation
- Full audit package delivered and accepted by investor legal team
- Entire program deployed 3 weeks ahead of the target date
0
AI systems classified in 2 weeks
0
weeks to full governance program
0
domains delivered in parallel
3wk
ahead of target delivery date
"Redefine turned our biggest due diligence liability into one of the strongest parts of our data room. Investors who flagged governance as a concern in the first meeting had no follow-up questions by the close."
Marcus Almeida
Chief Technology Officer, Apex Financial Technologies
What Was Delivered
Three things that separate our ai governance and risk consulting from everyone else's.
We build governance programs that survive contact with reality.
Most governance engagements produce a framework document and call it done. We stay through deployment, measure whether controls actually work, and adjust when they do not. The deliverable is a running system, not a presentation.
- Embedded through production deployment, not just design
- Controls measured against live system behaviour from week one
Your engineers own every asset we build. Zero lock-in, full code handoff.
Every policy template, registry schema, pipeline integration, and reporting script transfers to your team at project close. Your internal team can modify, extend, or replace any component without coming back to us.
- All source code, schemas, and configuration transferred at handoff
- Training sessions for your team included in every engagement
Regulatory fluency across all six major frameworks, not just one jurisdiction.
We track the European Union Artificial Intelligence Act, General Data Protection Regulation, sector-specific financial services guidance, United States executive orders on AI, healthcare privacy obligations, and National Institute of Standards and Technology framework revisions in real time. Your compliance mapping stays current without extra effort from your team.
- Six regulatory frameworks mapped and maintained continuously
- Alert system flags your program when guidance changes
Also From Redefine
Questions we hear before every engagement.
If something is not answered here, tell us your situation in the form below and we will respond within one business day.
Submit brief → call within 48 hours → scoped proposal in 3 days → Sprint 1 within 1 week of sign-off
For most enterprises with 10 to 50 active AI systems, a full six-domain governance program takes 8 to 14 weeks. Larger portfolios or those requiring deep regulatory mapping in multiple jurisdictions typically run 16 to 20 weeks. We can deliver a scoped policy layer and risk registry in as few as 4 weeks for organisations that need something auditable quickly.
No. Most clients come to us because they lack that internal capacity. We embed alongside your existing legal, technology, and operations leads, identify the right internal owners, and build the governance infrastructure your team then manages. We include training and documentation so those owners are confident from day one.
Our compliance mapping covers the European Union Artificial Intelligence Act, General Data Protection Regulation, United States National Institute of Standards and Technology Artificial Intelligence Risk Management Framework, sector-specific financial services guidance from relevant regulators, healthcare privacy obligations including the Health Insurance Portability and Accountability Act, and emerging state-level artificial intelligence legislation. We update compliance mapping continuously as guidance evolves.
Everything transfers to your team. Policy documentation, risk registry schemas, data pipeline integrations, monitoring dashboards, audit report templates, and incident playbooks are all delivered in editable formats your team owns outright. We do not use proprietary platforms or lock any deliverable behind a continued engagement.
Your team's time investment across a full build is typically 3 to 4 hours per week: one sprint review, asynchronous feedback on documentation and policy drafts, and a final sign-off session. We handle discovery interviews, framework design, technical integration, and compliance mapping independently. We do not book recurring status calls unless your programme governance requires them.
Yes. Retrofitting governance to existing deployments is one of the most common engagement patterns we run. We start with a discovery audit of your current estate, classify every system, identify the highest-priority gaps, and build controls in order of risk severity. Live systems get monitoring and controls deployed first; policy and documentation follow in the same sprint cycle.
Our ai assessment services: a good fit, honestly assessed.
This engagement is designed for a specific type of organisation. Here is a direct answer on whether that includes you.
Good fit for your organisation if...
- You have 5 or more AI systems in production or active development
- You are facing investor due diligence, regulatory review, or an internal audit on AI governance
- Your AI program is scaling faster than your risk and compliance processes can follow
- You want your internal team to own and maintain governance long-term without external dependency
- You operate in financial services, healthcare, insurance, or another regulated sector where AI accountability is a legal requirement
Not a fit if...
- You need a one-time policy document with no operational implementation
- You are a solo operator or very early-stage team with fewer than 3 AI tools in use
- Your budget is pre-revenue and cannot support a structured multi-week engagement
- You need a complete governance program delivered and running in under 3 weeks
- You are looking for ongoing managed governance with no internal ownership transfer
Not sure where you fall? Tell us your situation below and we will be straight with you about whether our ai governance and risk services fit. Go to the brief form →
From brief to proposal in 3 business days.
Submit Your Brief
Describe your current AI estate, your governance gaps, and any regulatory or investor deadlines. Takes approximately 5 to 7 minutes.
Scoping Call Within 48 Hours
A senior consultant reviews your brief and schedules a 45-minute call to understand your program in detail before any proposal is written.
Scoped Proposal in 3 Days
Line-by-line proposal covering scope, domain coverage, timeline, team structure, and total investment. No commitment required to receive it.
Sprint 1 Within 1 Week of Sign-Off
Discovery and AI estate classification begins immediately after sign-off. Your risk registry takes shape in the first two weeks.
Brief received.
We will review your AI program and send a scoped proposal within 3 business days.
What best describes your current situation?
Call within 48 hours
A senior consultant reviews every brief before we call.
Scoped proposal in 3 days
Line-by-line scope, timeline, and pricing. No placeholders.
42 enterprise programs delivered
Across financial services, healthcare, and technology sectors.
Full code ownership
Every asset transferred to your team at handoff. Zero lock-in.