AI security and governance
AI security consulting and red teaming for AI agents and LLM apps
Chatbots, AI agents and the AI tools your staff use every day open new ways to leak data and misuse your systems. We test them the way an attacker would, help you fix what we find and set up the governance regulators and customers now expect.
What you get
- AI red teaming and prompt injection testing
- Agent permission and tool-access review
- Shadow AI discovery and usage policy
- EU AI Act, ISO/IEC 42001 and NIST AI RMF readiness
Why AI systems need their own security testing
A classic penetration test looks for weaknesses in code and infrastructure. AI systems add a new attack surface: the instructions and data the model reads. An attacker can hide instructions in an email, a web page or a document and make an agent reveal data or take actions you never approved. The UK's National Cyber Security Centre warns that prompt injection may never be fully mitigated, so each system needs limits that contain the damage.
Unapproved AI use adds a second risk. In IBM's 2026 research, 43% of data breaches involved shadow AI: AI tools staff use without approval (IBM, Jul 2026).
Our AI security consulting brings the discipline of a security consultancy to AI: a written scope, findings ranked by risk, fixes your developers can apply and a retest to confirm them.
AI security consulting services
We test AI systems whoever built them, with your permission and a written scope.
AI red teaming
We attack your AI agents, chatbots and LLM apps with prompt injection, jailbreaks, data extraction and tool misuse, and report each finding with its risk and a fix.
Prompt injection testing
We test each input the model reads, including emails, files, web pages and retrieved documents, for hidden instructions that change its behavior.
Agent permission and tool-access review
We map what each agent can read, write and trigger, remove access it doesn't need and add approval steps for high-impact actions.
Third-party tool and MCP server review
We check the plug-ins, integrations and Model Context Protocol (MCP) servers your agents use for tampering, excessive permissions and unsafe data flows.
Shadow AI discovery and policy
We find which AI tools your staff use, assess the data they share and write a usage policy people can follow.
AI governance and compliance readiness
We map your AI systems to the EU AI Act, ISO/IEC 42001 and the NIST AI Risk Management Framework, then build the documentation and controls they call for.
What you receive from an AI security assessment
Every AI security consulting project ends with results your developers and your leadership can use.
- A written report with each finding, its risk rating and the fix.
- Proof-of-concept examples your developers can reproduce.
- A retest after you apply the fixes.
- An inventory of your AI systems and a risk register for governance.
- A short briefing for your leadership team.
From audit to launch in four stages
- 01 · 1–2 weeks
Opportunity and risk audit
We interview your team, map the workflows and rank AI opportunities by payback and risk.
You get: Ranked use cases, ROI model, risk map
- 02 · 4–6 weeks
Pilot with clear success criteria
One agent and one workflow, connected to your real systems and measured against the goal we agreed on. Then you decide whether to continue.
You get: Working agent, results report, go/no-go decision
- 03 · 2–4 weeks
Secure launch
We harden, attack-test and monitor the agent and train your staff before it talks to a single customer.
You get: Security report, operating guides, launch
- 04 · Ongoing
Run and improve
We track quality, cost per workflow and new risks, and keep improving the agent. Short contracts, no lock-in.
You get: Monthly performance and cost report
AI security and red teaming FAQ
What is AI red teaming?
AI red teaming means testing an AI system the way a real attacker would. We try to make it leak data, ignore its instructions, misuse its tools or produce harmful output, then report what worked and how to fix it.
What is prompt injection?
Prompt injection is an attack where someone hides instructions in content an AI reads, such as a message, an email or a document, to change what the AI does. It tops the OWASP Top 10 for LLM applications.
Do you test AI systems built by other vendors?
Yes. We test chatbots, agents and LLM apps whoever built them, with your permission and a written scope. For third-party AI tools, we test your configuration and the data you expose to them.
Does the EU AI Act apply to my company?
It can apply if you place AI systems on the EU market, use them in the EU, or their output is used in the EU, even if your company is based elsewhere. Article 50 transparency duties have applied since August 2, 2026. High-risk rules apply from December 2, 2027, or from August 2, 2028 for AI in regulated products. We map your systems to the obligations that apply to you.
How long does an AI security assessment take?
A focused test of one chatbot or agent takes 1–2 weeks in most cases, including the report. A full AI governance program runs in stages over a longer period.
Can you help with ISO/IEC 42001 certification?
We prepare you for it. We build the AI management system, policies, risk assessments and records the standard requires. An accredited certification body performs the audit itself.
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Free 30-minute assessment
Find the one workflow worth automating first.
Tell us how your team works. We'll come back with two or three AI opportunities, the risks to watch and a rough payback estimate. No obligation.
- A senior engineer replies within one business day
- We can sign an NDA before you share details
- No fixed packages, every quote tailored to you