Clinical systems · Clinical decision support AI
Glass Health
Glass Health makes clinical AI software that drafts differential diagnoses and assessment-and-plan notes with cited evidence and writes visit notes from recorded encounters, sold on published monthly plans.
Strong fit
- Primary care and hospital medicine clinicians who want help drafting a differential diagnosis and a plan
- Small practices that want AI visit notes and clinical decision support at a published monthly price
- Software teams that want a clinical reasoning API to build into their own products
Weak fit
- Health systems that want published outcome studies before adopting a clinical AI tool
- Organizations that want a large vendor with a long support record
- Clinicians who only want a dictation tool
Bottom line
Glass Health, based in San Francisco, California, makes AI software that drafts a differential diagnosis and a treatment plan from a patient summary, citing its sources, and also writes visit notes from recorded conversations. It publishes monthly prices for individual clinicians. It fits clinicians and small practices that want clinical reasoning help and a scribe in one tool, with the caution that public evidence of results is thin.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Dereck Paul, a physician who trained at the UCSF School of Medicine and Brigham and Women's Hospital, founded Glass Health in 2021 with Graham Ramsey. A clinician types a patient summary or records a visit, and Glass drafts a ranked list of possible diagnoses and an assessment and plan, with citations to the evidence it used, so the clinician can see why each item is there. A team of physicians writes and checks the clinical content behind its answers. Glass also writes visit notes from the recorded conversation.
Glass went through Y Combinator in early 2023 and raised a $5 million seed round led by Initialized Capital that September. It added a developer API in February 2025, connects to athenaOne, eClinicalWorks, Epic, and Elation, and in 2026 launched Glass for Patients, a version for patients themselves. Glass publishes few results from customers.
Compare OpenEvidence when doctors mainly want free, cited answers to clinical questions, and Doximity when a health system wants physician messaging and telehealth calling with a clinical AI tool attached.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| OpenEvidence | 8.4 | 8.8 |
| Doximity | 6.9 | 7.1 |
| Glass Health | 6.8 | 6.9 |
Pricing
| Item | Detail |
|---|---|
| Model | Published monthly plans for clinicians; developer API and health-system deployments quoted separately. |
| What usually drives cost | Plan level (Lite, Starter, Pro, or Max), scribing and decision support usage limits, and EHR integration, which comes with the Max plan. |
| What to ask in diligence | Annual pricing for a group, what the usage limits mean in visits per month, and whether patient data is used to train models. |
| Published pricing | Published on glass.health. |
Published plans are Lite at $0, Starter at $20, Pro at $90, and Max at $200 per month. Lite and Starter carry sponsored content; Pro and Max do not.
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Glass Health to function | |
| Physician lead for AI tools | Someone should review its suggestions. |
| Policy on AI in clinical decisions | Clinicians need clear limits. |
| EHR integration plan | Max plan connects to the record. |
| Patient consent process for recording | Scribing records the visit. |
| Way to report wrong suggestions | Errors should reach the vendor. |
| What will maximize your value | |
| Start with complex visits | Diagnosis help adds the most there. |
| Check citations on unfamiliar cases | The sources show its reasoning. |
| Compare note time before and after | Shows whether scribing helps. |
| Deal-breakers | |
| Needs published outcome studies | |
| No physician oversight of AI | |
| Wants dictation only | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Clinician sign-up | Same day |
| 2 | EHR connection on Max plan | Days to weeks |
| 3 | Group rollout and guidance | 1-2 months |
Leadership
Methodology
| Weight | Factor | What it measures |
|---|---|---|
| 35% | Customer outcomes | Whether buyers get measurable operational or clinical-workflow results after go-live |
| 30% | Product | Capability depth, reliability, and fit for the job the category buys |
| 20% | Implementation | How hard it is to stand up, integrate, train, and stabilize |
| 15% | Pricing clarity | Whether a buyer can model total cost without a mystery quote |
| Label | Meaning |
|---|---|
| Highly recommend | Strong outcomes and product with manageable caveats |
| Recommend | Solid fit for the right buyer; know the tradeoffs |
| Conditional | Only with a specific use case or heavy caveats |
| Not recommended | Avoid for most buyers in this category |
Read our full methodology for how we weight scores and assign recommend labels.