Labs
Working models, not slides. Each lab shows how an advisory approach behaves on realistic systems — click through it, change things, and see the consequences.
Can this AI agent be trusted?
An AI agent that pays supplier invoices is tricked by a fake invoice. Watch the checks stop the payment, the agent’s authority drop automatically, and the bank refuse to let it act alone — the full loop of verifying an AI agent before and while it works.
- ID card: who the agent is, who is responsible for it, and what it is built from
- Job & limits: exactly what it may do, and how much it may spend
- Entrance test: 1,240 situations, including the most common ways agents are tricked
- Live checks: every action checked before it happens — try tricking it yourself
- Trust level that drops automatically when the agent misbehaves
- The bank’s check, and an audit trail nobody can secretly change
Three fictional AI agents at a fictional lender: supplier payments, debt collection and customer checks. The digital signatures and locked records use real cryptography in your browser.
Fictional company and synthetic data. Framework references are indicative and not legal advice.
AI Governance Workbench
Every AI application against the EU AI Act, ISO/IEC 42001, NIST AI RMF and the OECD AI Principles — in one matrix. Adherence is decided by runtime evaluation metrics measured on each application, with documents as secondary evidence.
- Organisation matrix: % adherence for every application × framework
- Drill down by framework or by application to each control
- Runtime metrics and documents side by side, with evidence for every finding
- Industry-standard metrics: OWASP LLM Top 10, RAGAS, DeepEval, C2PA, Fairlearn and more
- Fix once, close many — remediation ranked across all frameworks
- What breaks if…? — preview the governance impact of a model, prompt or tool change
Four GenAI applications: a RAG assistant, a high-risk letter writer, an agent with tools and a generative-media studio.
Fictional company and synthetic data. Framework references are indicative and not legal advice.
In the lab next
AI & Data Architecture
Reference architectures for production RAG and agentic systems.
AI Capability & Delivery
From pilot to production: delivery model and capability build.