Diagnify review
A clinician-facing reasoning aid that structures cases and links differentials to evidence.
Reviewed by iTechGuides Editors · Editorial team · Updated Nov 2026
Diagnify is an AI clinical decision-support product for qualified health professionals who want help organizing a presentation and examining possible explanations. It structures symptoms, history, examination findings, and clinical context into a problem representation, then raises red flags and supports comparison of differential diagnoses as new findings arrive. Investigation planning can help distinguish leading possibilities. The product is positioned as a reasoning aid for clinician-led case review, not as an autonomous diagnostic or treatment system.
A central feature is the combination of a clinically fine-tuned model with a separate evidence-retrieval layer. Clinicians can review source-linked guidance and evidence alongside the system’s assumptions, uncertainty, and alternative possibilities. This supports scrutiny of the reasoning rather than asking users to accept a single answer at face value. Diagnify also supports interactive, voice, and consultation-transcript workflows, giving teams more than one way to bring a case into the review process. Treatment recommendations are listed among its decision-support capabilities, but outputs still require professional judgment.
The product is described as being in evaluation, so it is a better fit for clinicians assessing an emerging decision-support workflow than for teams seeking a mature, established deployment. It is cloud-based and available on the web. Pricing is handled through contact with sales; private API access is reviewed by use case. The vendor also mentions a free pilot for separate practice software, which should not be taken as a free plan for Diagnify’s clinical decision-support product. Choose it if transparent differential reasoning and reviewable evidence are priorities; look elsewhere if you need an established system or autonomous clinical decisions.
Diagnify pros and cons
- Where it wins
- Structures clinical context and updates differentials as findings arrive
- Flags red flags and supports investigation planning
- Shows assumptions, uncertainty, alternatives, and source-linked guidance
- Where it doesn't
- The clinician product is currently in evaluation
- Pricing is contact-sales, with API access reviewed by use case
- Outputs require clinician review; it is not an autonomous diagnostic system
Diagnify fact sheet, pricing and score →
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