Plausible and wrong is most dangerous in medicine.
Triage, documentation, decision support. When your AI's outputs touch patient safety, we test them against the judgement of practising clinicians, and give you the evidence.
The healthcare AI we validate
Symptom assessment & triage
Tools that assess symptoms and route patients, where under-triage is a safety incident and over-triage swamps the service.
Clinical documentation
Ambient scribes and summarisers, where a dropped negative or a wrong dose in the note becomes part of the record.
Decision support
Systems that suggest differentials, pathways, or next steps, where a clinician's trust has to be earned and deserved.
Patient communication
Tools that explain conditions, results, and treatment to patients, where clarity, accuracy, and tone all carry clinical weight.
Mental health support
Conversational tools for mental health, where the cost of a wrong response is measured in people, not percentages.
Medication & interactions
Checks on prescribing, dosing, and interactions, where the standard is the BNF, not a best guess.
Validation is mapped to the safety and evidence standards healthcare answers to, so your evidence supports conversations with clinical safety officers, information governance, and NHS buyers.
- MHRA guidance on software and AI as a medical device
- Clinical safety standards DCB0129 and DCB0160
- NICE evidence standards framework for digital health
- UK GDPR rules for special category health data
- EU AI Act obligations for health-related AI
- Professional standards: GMC, NMC, and HCPC expectations of clinicians
Reviewed by clinicians who still see patients.
Practising doctors, psychologists, therapists, pharmacists, and allied health professionals grade your AI's outputs the way they'd review a junior's notes: against the standard their regulator and their patients hold them to.