AI belongs in dentistry only when it’s safe by design.
We build clinical AI for dental practice — and we hold it to the standards patients deserve. This is where we share how clinical safety, data protection, regulation, and human oversight come together in practice.
Clinical safety standards
Built under the NHS clinical-risk-management standards (DCB0129/0160), with a named Clinical Safety Officer and a living hazard log.
Data protection by design
Special-category patient data, encrypted in transit and at rest, minimised by default, with the option to never store audio at all.
Human in the loop
AI drafts; the clinician decides. Nothing enters the record without a clinician reviewing and approving it first.
Regulated and accountable
MHRA-registered, ICO-registered, with audit trails and post-market surveillance that make every decision inspectable.
Our safety commitment
Clinical AI should make care safer, not riskier. That means assuming the software can fail, designing so a clinician always catches it, protecting patient data as the sensitive information it is, and never using technology in ways its makers — or the regulator — forbid. These articles explain exactly how we put that into practice.
Safety articles
Plain-English explanations of the precautions behind responsible dental AI.
Clinical Safety by Design: DCB0129 and DCB0160 in Dental AI
How the NHS clinical-risk-management standards apply to AI software in dentistry, and why a named Clinical Safety Officer matters.
Keeping Patient Data Safe: GDPR, Encryption and Data Minimisation
Patient audio and clinical notes are special-category data. Here is the layered approach that keeps it protected end to end.
MHRA Class I Registration: What It Means for an AI Dental Tool
Why some clinical software is a regulated medical device, what Class I registration involves, and how it constrains the technology you can use.
Human in the Loop: Why the Dentist Always Has the Final Word
AI should draft, never decide. How review-before-commit and clear authorship keep clinical accountability with the clinician.
Guarding Against AI Errors and Hallucinations
Language models can invent plausible-sounding detail. The engineering and prompt safeguards that keep fabricated content out of clinical notes.
Audit Trails and Version History: Accountability You Can Inspect
Who recorded what, when, and what the AI originally proposed versus what the clinician changed — and why that record matters.