AI security
Governance, risk assessment and adversarial testing for AI systems and autonomous agents, aligned to ISO/IEC 42001 and tested against how these systems actually fail.
Secure your AI programme- Standards
- ISO/IEC 42001 · NIST AI RMF
- Testing
- Adversarial, tool-aware
Why this matters now
AI is already in use inside most organisations, usually before governance catches up. AI security gives you control without blocking work that is genuinely useful.
Everything in AI security
7 pages. Each one states what it covers, who delivers it and what you get at the end.
AI governance
A live inventory, named ownership and a lightweight approval route for AI systems, so useful work continues and shadow adoption…
Read moreAssessment and testingAI risk assessment
Assessment of each use case for security, privacy, legal and model risk, covering what data reaches the model, from where,…
Read moreAssessment and testingAI agent security
Trust boundaries, least-privilege tool permissions and human approval points for autonomous workflows, reviewed against the irreversible actions an agent can…
Read moreAssessment and testingPrompt injection testing
Adversarial testing of direct and indirect injection paths, including documents and web content, tool abuse and data leakage, with a…
Read moreDeployment and peopleSecure AI deployment
Controls built into the implementation rather than added afterwards: identity, data boundaries, model access, prompt and tool-call logging, and proper…
Read moreGovernanceAI policy development
Acceptable use, data classification, approvals, procurement questions and incident handling, written in a page staff will actually read.
Read moreDeployment and peopleAI security training
Role-specific sessions for boards, developers, security teams and general staff, worked through your own use cases rather than generic examples.
Read moreHow the work runs
The same sequence on every engagement, so you know what happens next.
Inventory
Establish what AI is actually in use, including tools adopted without approval.
Assess
Evaluate each use case for security, privacy, legal and model risk.
Control
Apply proportionate controls: policy, access, logging, approval points and monitoring.
Test
Adversarial testing against the deployed system, including indirect injection paths.
Govern
Reporting, review and change control so governance keeps up with adoption.
Technology partners
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Before you enquire
How quickly can this start?
Who actually does the work?
How is this priced?
Secure your AI programme
Tell us the outcome you need. We will tell you honestly whether we are the right people for it.