Applied AI · Testing & inspection
AI Strategy & Advisory for Testing & inspection
Cut through the AI noise. Find the few use cases worth doing, ship them safely, and govern them properly.
Why it matters in testing & inspection
Accreditation and data integrity are the business. A lab's results are only worth what their traceability and impartiality can withstand under scrutiny.
- →Protecting data integrity and audit trails end-to-end through LIMS and instrumentation
- →Maintaining accreditation while modernising legacy systems and integrations
- →Securing OT and lab equipment that was never designed to be networked
- →Scaling digital services without undermining impartiality or chain-of-custody
What you get
- ✓AI opportunity assessment — use cases ranked by value, risk, and feasibility
- ✓Pragmatic build vs buy vs fine-tune decisions, with cost modelling
- ✓Reference architecture for LLM/agent systems: evals, guardrails, and data handling
- ✓AI governance aligned to the EU AI Act and your sector's rules
- ✓Proof-of-concept to production — with the bar set at 'actually useful'
Frameworks & standards
ISO/IEC 17025ISO 27001UKAS expectationsCyber Essentials
How we work in testing & inspection
We bring security and architecture discipline that respects accreditation realities — hardening the systems your results depend on without breaking the controls your assessors rely on.