AI Security Services - AI security for businesses using LLMs and agents
AI tools and agents are already inside most companies, often without anyone checking what data they can see or what they are allowed to do. We help you find out, close the gaps, and adopt AI on terms you control. We work from recognised frameworks such as the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework.
AI Risk Assessment
You can't secure what you haven't mapped. We identify where AI is used in your business, what data it touches, and which risks are worth your attention first.
- AI usage and data-flow mapping. Which tools, models and integrations are in use, officially or not, and where your data goes.
- Risk prioritisation. A short, ranked list of what to fix first, in plain language for both management and engineers.
- Vendor and contract review. What your AI suppliers retain, train on, and promise, compared with what you assumed.
LLM Security & Agent Testing
If you are building on top of a language model, we test it the way an attacker would, and report what we find with clear remediation steps.
- Prompt injection and jailbreak testing. Direct and indirect injection through documents, web content and tool outputs.
- Data exposure testing. Whether retrieval (RAG) setups and system prompts reveal information to users who should not see it.
- Agent permission review. What each agent can read, change and trigger, and whether that is the minimum it needs.
Secure AI Architecture
When you are about to build or integrate AI, we help you design it so a single failure does not become a breach.
- Access control for AI. Least-privilege design for models, agents and the data they retrieve.
- Guardrails and logging. Practical input and output controls, plus the audit trail you need to investigate problems.
- Build with security in. Our product development team can implement the design when you want us to.
Building With AI Agents, Safely
We use AI agents in our own development work, so we know where they speed a team up and where they need limits. We help your developers get the speed without handing an agent the keys to everything.
- Guardrails for coding agents. Sensible permissions, sandboxing and secret handling, so an agent can do its job without access to what it doesn't need.
- Workflows that keep quality up. Where review, testing and human sign-off fit when part of the code is written by AI.
- Team setup and onboarding. Practical conventions and a short playbook your developers can start using right away.
AI Policy & Team Training
Rules nobody understands don't get followed. We help you set sensible guidelines and make sure your people know them.
- Acceptable-use policy. A short, usable policy for what staff may and may not do with AI tools.
- Awareness training. Practical sessions for staff and developers, based on realistic scenarios.
- Regulatory orientation. A clear starting point on how GDPR and the EU AI Act apply to your use of AI. This is guidance, not legal advice.
The risks - Where AI goes wrong in a business
Most AI incidents aren't exotic attacks. They're ordinary access and data problems that a model makes easier to trigger.
- Prompt injection. Text in an email, web page or document can steer your assistant into ignoring its instructions or leaking what it knows.
- Data leakage. Staff paste customer data into public tools, and internal documents surface in answers to people who should never see them.
- Over-powered agents. An agent with broad access to mail, files or systems turns one successful trick into a real incident.
- Shadow AI. Tools adopted without anyone checking where the data goes, who retains it, or what the contract says.
- Third-party models and plugins. Every model, plugin and vendor in the chain is a supplier whose security you inherit.
- Compliance exposure. GDPR and the EU AI Act put obligations on how you use AI, whether or not you built it.
How we work - Start small. Go deeper where it matters.
Every engagement starts with a short, fixed-scope step, so you know what you are getting before you commit to more.
- 1. AI risk check. A short working session. We map the AI tools and data flows in your business and give you a prioritised list of risks.
- 2. Assessment & testing. A deeper review of your LLM apps, agents and integrations, including hands-on testing against known attack patterns.
- 3. Fix & follow-up. We help you close the gaps, build safer architecture where needed, and check back as your AI use changes.
FAQ - Common questions about AI security
- What is prompt injection?
- Prompt injection is when text inside an email, web page or document tricks an AI assistant into ignoring its instructions, for example to reveal information or take an action it should not. It is one of the most common risks for LLM applications and agents.
- We only use ChatGPT or Copilot. Do we need AI security?
- Probably yes, in a lighter form. Even off-the-shelf tools raise questions about what data staff paste in, what the tool can access in your systems, and what your vendor retains. An AI risk check answers those questions.
- What does an AI risk check involve?
- A short working session where we map the AI tools and data flows in your business, then give you a prioritised list of risks and next steps. It is a fixed-scope first step, so you know what you are getting before committing to more.
- Can you help our developers use AI coding agents safely?
- Yes. We use AI agents in our own development work and help teams set up permissions, sandboxing, secret handling and review workflows, so they get the speed without giving an agent access to everything.