AI governance that your engineers can follow and your auditors can check.
We help you define who owns each AI system, what it may do, where people review its output, and how decisions are recorded — then build those controls into the systems themselves rather than leaving them in a policy document.
- AI system inventory
- Risk tiering and review rules
- Human oversight design
- Data and privacy controls
- Audit logging and traceability
Where this helps
What we deliver
How it works
- 01
Map what exists
We interview owners and review systems to build the inventory and understand current controls, contracts and data flows.
- 02
Agree the framework
With legal, security and business owners we set risk tiers, review requirements and decision rights that fit your organization's size.
- 03
Embed controls in systems
We implement logging, access control, redaction and approval steps in the priority systems, not just in documents.
- 04
Test and rehearse
We run review scenarios, including an incident drill and a mock audit request, to check the controls produce the evidence they should.
- 05
Hand over operations
Owners get runbooks, review cadences and templates so governance continues as new AI systems are added.
Design decisions we make with you
Proportionality
Governance effort should match risk. An internal drafting assistant and a system that affects customer eligibility do not need the same process.
Decision rights
Who can approve a new model, a new data source or a change in autonomy — written down, with a named backup.
Provider data terms
Whether prompts and outputs may be retained or used for training by a provider, and which contract or deployment option controls that.
Evidence over attestations
We favor controls that produce logs and test results over checklists that rely on people remembering to fill them in.
Regulatory alignment
We map your controls to the frameworks and regulations you name, and flag where specialist legal advice is needed. We do not issue compliance certifications.
Applications
Related capabilities
- Customer Support AgentsResolve routine customer inquiries from your policies and live account data, taking approved actions and handing everything else to your team.
- Fraud & Risk SignalsScore transactions, claims or applications for risk and send the suspicious ones to investigators with the reasons attached.
- AI Consulting & StrategyFind the AI opportunities worth funding, test whether your data and systems can support them, and leave with a sequenced roadmap.
- Enterprise & Private AIAI deployed with the data isolation, access control and operational ownership your security and compliance teams require.
- MLOps & LLMOpsEvaluation, release, monitoring and cost control for predictive models and LLM applications once they are in production.
- Is your data ready for AI? A practical assessmentYour data is ready enough for an AI project when the specific data that one use case needs is accessible, understood, representative of real work, of known quality and permitted for that use. You do not need a perfect data estate first; you need to assess readiness one use case at a time.
- From AI pilot to production: a readiness checklistA pilot is ready for production when it has a named owner, an evaluation set that reflects real work, integrations that run under their own identity, documented controls, and a plan for monitoring, cost and support. If any of those are missing, fix them before you scale.
Questions buyers ask
No. We design and implement governance controls and help you produce the evidence reviewers ask for. Legal interpretation and formal certification remain with your counsel and auditors.
Done well, it speeds them up. Clear risk tiers let low-risk projects proceed with light review, and pre-approved patterns for data and models remove repeated debates.
Yes. The inventory, data rules and review requirements apply to purchased tools too. Where a vendor product lacks logging or controls, we note the gap and suggest mitigations.
Governance covers ownership, oversight and accountability; security covers access, threats and infrastructure. They overlap, and we coordinate with your security team. See trust and security.
Discuss this capability with an engineer.
Tell us about the workflow or product. We reply with questions, a suggested first step and who would work on it.