Cybersecurity and Infrastructure

AI Security and Responsible AI

AI systems bring their own failure modes. These are the controls that keep them safe to use.

How We Work, Step by Step
  1. 1Define the use
  2. 2Set data rules
  3. 3Design the guardrails
  4. 4Test adversarially
  5. 5Monitor and review

What We Do for You

  • Write the AI use policy and the approval path.
  • Set data rules for what may and may not reach a model.
  • Design agent permissions and action logging.
  • Red-team your AI systems, including prompt injection.
  • Set up monitoring for drift, misuse and cost.

How this is bought: Bought as an assessment first, then a project priced from what the assessment finds. Build an estimate for your case.

Our Approaches Explained

Prompt injection defence

Treating anything a model reads - documents, web pages, tool output - as untrusted input rather than instruction.

Output handling and grounding

Answers tied to approved sources, with limits on what the model may assert.

Human-in-the-loop approval

A person approves consequential actions before they take effect.

Model and data governance

Recording which model version, which training or reference data, and who approved its use.

Data leakage prevention

Rules on what may be sent to a model, and where that data is processed and retained.

Access control on tools and agents

An agent holds only the permissions its task needs, and every action is logged.

Evaluation and red teaming

Deliberately trying to make the system fail before customers can, and recording the results.

Monitoring for drift and misuse

Watching how answers change over time and how the system is actually used.

Transparency to users

People are told when they are speaking with an AI and how to reach a person.

The Standards We Work To

NIST AI Risk Management Framework (AI RMF 1.0)ISO/IEC 42001 AI management systemsOWASP Top 10 for LLM ApplicationsEU AI Act risk tiers (where applicable)

We follow the structure and controls these standards describe. We do not claim to be certified against them - where you need a formal certificate, we prepare the evidence and an accredited body performs the audit.

What You Get

  • AI use policy and approval path
  • Data handling rules for AI systems
  • Agent permission design
  • Evaluation and red-team report
  • Monitoring and review schedule
Where We Usually Focus
AI uses with a written owner90%
Consequential actions requiring approval100%
Systems with logged actions95%

These are the areas clients most often ask us to improve. Your project sets its own targets, measured and agreed with you.

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