AI & Security Automation
For three years our work has focused on applied AI security engineering: putting frontier large language models — Claude, OpenAI, Gemini and Meta — to work on cyber security.
We develop, test and operate automated security testing using agentic AI and automation frameworks, including specialised security testing models. The same engineering powers AI-assisted vulnerability discovery, exploit and remediation reasoning, code review and finding triage — work that used to consume most of a tester’s or analyst’s day.
We design and run the plumbing that makes it reliable: agentic workflows, retrieval-augmented generation over your own documentation, vector databases, tool-use orchestration, prompt engineering and automated evaluation pipelines that measure whether the AI is actually right.
And we keep it governed. We deploy and operate frontier models and agents inside governed environments, including Azure AI Foundry with its evaluation and content-safety tooling, put operational AI security controls around them, and align your AI governance with the EU AI Act and ISO/IEC 42001.
ControlDesk, the GRC platform we built, is the same approach in production: purpose-built AI does the first pass of every assessment, and a person decides on the record.
What we build and run
- Automated, agentic AI security testing
- AI-assisted vulnerability discovery and exploit reasoning
- AI-assisted code review, remediation reasoning and finding triage
- AI-assisted security assessment frameworks
- Agentic workflows, RAG architectures and vector databases
- Tool-use orchestration and prompt engineering
- Automated evaluation pipelines
- Frontier models and agents on Azure AI Foundry, with evaluation and content safety
- AI governance and operational AI security controls — EU AI Act and ISO/IEC 42001
- First-pass supplier assessments, control mapping and evidence collection for GRC
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