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Understand where your clinical AI falls short.
For product, clinical and engineering teams that need an independent view of how an AI system responds in medicines and prescribing-related workflows.
When this is useful
You have a working prototype, a forthcoming pilot or release, or a response that raises a clinical concern. The question is whether the system handles the clinical context appropriately, and what to investigate next.
How the work runs
- Agree a scenario set and criteria matched to the intended use.
- Review outputs for clinically important omissions, unsupported claims, unsafe reassurance and escalation.
- Prioritise findings, record evidence and identify further testing or changes worth investigating.
What your team receives
- A scoped evaluation brief and scenario coverage map.
- Traceable findings, clinical rationale and prioritised recommendations.
- A handover with limitations, unresolved questions and next testing priorities.
Scope and limits
A small qualitative evaluation does not establish whole-system accuracy or safety. Statistical performance estimation, multiple evaluators and larger testing programmes require a separate scope.
Start with your clinical AI question.
Send a short, non-confidential overview. I'll assess fit and discuss a written scope, fee and timing.