We test your AI systems the way an attacker would: prompt injection, data leakage, agent abuse, MCP server hardening — and deliver a prioritised remediation report your engineering team can actually ship.
We try to make your AI assistant say what it shouldn't, leak what it shouldn't, and do what it shouldn't. We document every successful attack.
If your AI can call tools — send emails, write to databases, execute code — we test what happens when an attacker controls the prompt. Most teams underestimate this.
MCP servers expose tools to AI agents. We audit yours for authentication gaps, over-permissive scopes, and tool descriptions that leak sensitive context.
We map your AI surface area: assistants, agents, MCP servers, tool integrations, data flows. We agree on the rules of engagement.
Prompt injection, jailbreak, data exfiltration, tool abuse, MCP hardening tests. Every finding gets a reproducer.
Findings prioritised by impact and effort, with concrete code-level fix recommendations. Walk-through with your engineering team.
Six weeks later we re-run the failed tests against your fixes. You get a clean bill of health to share with your security team or board.
Classic pen-tests probe web apps, APIs and networks. AI systems break differently: a carefully crafted input in a customer ticket gets your support bot to quote internal documents. A link in an email makes your agent ship data to an external server. We bring the threat model, the test methodology and the reproducers — and hand you a report your engineering team can translate into pull requests.
Three situations where we typically get called in.
Customer-support bot with access to customer tickets. CTO wants to know whether prompt injection is a real problem before SOC-2 audit.
Internal agent with email-send permission. Board asks what happens if an employee uploads a malicious PDF.
MCP server with access to the production database. Lead investor wants security evidence before the funding round.
We test what classical pen-tests miss — and hand off every finding with a concrete fix.
We map your AI attack surface: assistants, agents, MCP servers, tool integrations, data flows. Before we test, we know where it can hurt.
Prompt injection, jailbreak, indirect injection via documents and websites, tool-call abuse. We use techniques that actually work in the wild.
If you already use guardrails, we check whether they hold. If not, we design the missing ones — system prompts, Bedrock Guardrails, output filters.
Findings prioritised by impact and effort, each with a concrete code-level fix. Walk-through with your engineering team. Optional re-test after 6 weeks.
scoped to complexity
A governed AI environment on your own AWS account: Bedrock with access to Claude and OpenAI (ChatGPT) models, Guardrails, audit logs and cost controls — set up in 4 weeks.
A digital team member that knows all your company documents and gives your staff the right answers instantly — around the clock.
A management platform for AI agents: deploy new agents independently, assign tasks, monitor results — no external vendor required.
Risk classification, AI register, DPIAs and governance committee setup — your documentation and processes ready for the regulator.
AI inside your own AWS environment — your keys, your data, no traffic to the public internet. For finance, healthcare and the public sector.
Stop paying for what you don't need. Audit your AI spend, implement caching, set budgets, and assign costs back to teams.
30 minutes, no obligation, no cost. We'll honestly tell you if and how we can help.