AI you can explain. And defend.
Governance is what lets AI move from pilot to production. We help you secure AI systems, evaluate their quality, monitor them in production, protect personal data and apply responsible AI practices, as engineering work built into the system rather than a policy document filed alongside it.
You're in the right place if…
- Organisations in regulated sectors that must show how AI decisions are made and controlled
- Security and risk teams asked to approve AI systems they did not design
- Leaders scaling AI from a few pilots to many teams who need consistent guardrails
- Teams already running AI in production without clear evaluation or monitoring
What gets in the way.
New attack surfaces
Prompt injection, data leakage and over-permissioned agents are risks traditional security reviews were not built for.
Quality nobody measures
Without evaluation, it is impossible to tell whether a change to a prompt or model made things better or worse.
Privacy obligations
Personal and sensitive data must be handled lawfully, minimised and kept within agreed boundaries.
No visibility in production
Cost, usage, failures and drift in answer quality go unnoticed until users complain.
AI Governance & Responsible AI, end to end.
AI security review
Threat modelling and testing for prompt injection, data exposure and excessive agent permissions.
Evaluation frameworks
Test sets, scoring and regression checks that measure accuracy, grounding and safety before each release.
Production monitoring
Tracking of quality, cost, latency, usage and failures, with logs that support audit and investigation.
Privacy and data protection
Data minimisation, redaction, retention rules and clear boundaries on where data may be processed.
Responsible AI practices
Fairness, transparency and human oversight built into design decisions and documented for stakeholders.
Governance operating model
Policies, approval workflows and an inventory of AI systems that scale as adoption grows.
A delivery approach you can plan around.
Assess
Review existing and planned AI systems against your risk, security and regulatory context.
Define guardrails
Agree the controls, evaluation criteria and approval points each class of AI system needs.
Engineer the controls
Build evaluation, monitoring, access control and data protection into the systems themselves.
Review continuously
Monitor in production, re-evaluate on every significant change and keep documentation current.
Ways to work with us.
Governance assessment
A review of your AI systems and practices, with a prioritised list of controls to put in place.
Controls implementation
Engineering the evaluation, monitoring and security controls into one or more AI systems.
Ongoing assurance
Regular evaluation and monitoring reviews as your AI estate changes.
Technologies we work with
- LLM evaluation and test harnesses
- Tracing and observability tooling
- Data redaction and classification
- Role-based access control and audit logging
- Cloud security services
AI Governance & Responsible AI: common questions.
Can you help with AI regulation?
We help you put the technical controls, evaluation evidence and documentation in place that regulations and internal policies typically require. Legal interpretation of a specific regulation should come from your legal or compliance advisers.
What does evaluating an AI system involve?
Building a set of representative test cases, defining how outputs are scored, and running those checks on every change to prompts, models or data, so quality is measured rather than assumed.
Does governance slow delivery down?
Done late, it does. Built in from the start, it removes the long security and risk reviews that usually stall pilots before production.
Can you review AI systems another team built?
Yes. We can assess existing systems, whoever built them, and recommend or implement the controls they are missing.
Let's talk about your ai governance & responsible ai needs.
Someone from our Data & AI practice will reply within one business day to talk through the use case.