OpenEvidence
by OpenEvidence
Point-of-care medical answer engine, free to licence-verified clinicians
OpenEvidence is a clinical answer engine that lets physicians ask natural-language medical questions and get cited, evidence-linked answers at the point of care. It is free to clinicians who verify a medical licence, monetised through pharmaceutical advertising and health-system contracts, and draws on licensed content from NEJM, JAMA, Wiley, Cochrane and the American College of Cardiology.
OpenEvidence, founded in 2021 by Daniel Nadler and headquartered in Cambridge, Massachusetts, is a clinical decision-support answer engine that has become the fastest-adopted physician application on record. Clinicians ask a question in natural language and receive a synthesised answer with inline citations back to the primary literature, delivered on web, iOS and Android. What separates it from a general-purpose chatbot is the corpus: OpenEvidence has signed content partnerships with the New England Journal of Medicine, JAMA and the AMA, Wiley, Cochrane and the American College of Cardiology, so answers are drawn from licensed full-text and multimedia sources rather than scraped abstracts. Two modes exist — Quick Consult for point-of-care lookups, and DeepConsult, launched alongside the July 2025 Series B, which reads many papers in parallel and assembles a research report using more than a hundred times the compute of an ordinary query. Access is free to any clinician who uploads medical licence documentation for verification; there is no paid consumer tier. Revenue comes from pharmaceutical and medical-device advertising at $70 to $1,000+ CPM plus enterprise health-system contracts, a model Sacra estimates produced roughly $150M annualised revenue in 2025 at about 90% gross margin, up 1,803% year over year. Scale is the headline: roughly 40% of US physicians use it daily, more than 10,000 medical institutions are on the platform, monthly clinical consultations reached about 20 million by January 2026, and a single 24-hour record of one million consultations was set on 10 March 2026. Enterprise Epic EHR deployments began with Sutter Health in February 2026, followed by Mount Sinai and Cedars-Sinai. A $250M Series D co-led by Thrive Capital and DST Global in January 2026 valued the company at $12B, taking total funding past $700M.
Health systems and physician groups that want an evidence-lookup layer their clinicians already use, ideally embedded in Epic — and individual licence-verified clinicians, who can adopt it with no procurement at all.
Cited, literature-backed answers to clinical questions in seconds at the point of care, from licensed journal content rather than a general web index, at no cost to the clinician.
At a Glance
- Category
- Industry & Government
- Pricing
- Free, Contact for pricing
- Target Market
- Physicians, Health System CIOs, Clinical Informatics Leaders, Residents and Fellows, Pharmacists
- Deployment
- Cloud-only
- Founded
- 2021
- Headquarters
- Cambridge, Massachusetts, United States
- Customers
- ~40% of US physicians use it daily across 10,000+ medical institutions, with roughly 65,000 new registrations per month in H1 2026
Key Features
- ✓Cited natural-language clinical answers
Returns synthesised answers with inline citations to primary literature, so a clinician can verify the source before acting.
- ✓Licensed journal corpus
Draws on NEJM, JAMA and AMA, Wiley, Cochrane and American College of Cardiology content under partnership rather than scraped abstracts.
- ✓DeepConsult deep research mode
Reads many papers in parallel using over 100x the compute of a standard query to assemble a doctoral-level research report.
- ✓Licence-verified free access
Clinicians upload medical licence documentation to unlock unlimited use with no subscription, removing procurement from adoption entirely.
- ✓Epic EHR embedding
Enterprise deployments put natural-language evidence search inside the patient chart, so clinicians never leave the EHR.
- ✓Multi-platform access
Available on web, iOS and Android, with Japanese-language support added in early 2026 for non-English clinical use.
Capabilities
Use Cases
- •Bedside evidence lookup
A clinician mid-encounter asks a treatment question and gets a cited answer in seconds instead of deferring the decision.
- •Checking current guidance before prescribing
Confirm whether recent trial evidence or a guideline update has changed the standard of care for a given presentation.
- •Literature synthesis for rounds or M&M
DeepConsult assembles a multi-paper report on a clinical question, replacing hours of manual database searching and screening.
- •Health-system-wide evidence layer in the EHR
Sutter Health, Mount Sinai and Cedars-Sinai embedded it in Epic so evidence search happens without leaving the patient chart.
- •Trainee education and case preparation
Residents and fellows use cited answers to prepare cases and understand the evidence behind a recommendation, not just the recommendation.
Ideal For
Best For
- ✓Point-of-care evidence lookup during a patient encounter, where a full literature search is not practical
- ✓Keeping up with fast-moving guidance in a subspecialty without reading every journal issue
- ✓Health systems wanting an evidence layer embedded in the Epic chart, as deployed at Sutter Health, Mount Sinai and Cedars-Sinai
- ✓Deep literature synthesis via DeepConsult, which reads many papers in parallel to assemble a research report
- ✓Residents, fellows and trainees who need cited answers rather than an uncited chatbot response
Not Ideal For
- ✗Patients and the general public — the product is explicitly positioned as a tool for verified experts and is not designed for self-diagnosis from entered symptoms
- ✗Clinical workflows that require differential diagnosis generation or drug dosing calculators; independent reviewers note these are absent and that teams usually pair it with a broader clinical decision support platform
- ✗Organisations that cannot accept pharmaceutical and medical-device advertising adjacent to clinical answers, since that advertising is the core revenue model
- ✗Buyers needing a documented public API or programmatic integration outside the enterprise Epic embed
- ✗High-stakes complex subspecialty reasoning used unsupervised — a December 2025 preprint reported 41% accuracy for DeepConsult and 34% for Quick Consult on subspecialty scenarios
Deployment
Market & Ratings
~40% of US physicians use it daily across 10,000+ medical institutions, with roughly 65,000 new registrations per month in H1 2026
Market Analysis
Pros
- ✓Free at the point of care with only licence verification required, so adoption needs no budget, contract or IT project
- ✓Content is licensed from NEJM, JAMA and the AMA, Wiley, Cochrane and the American College of Cardiology rather than scraped, which is the substance behind the citation quality
- ✓Adoption at genuinely unusual scale — about 40% of US physicians daily, 10,000+ institutions, ~20 million monthly consultations as of January 2026
- ✓Rated 4.3 out of 5 and ranked second of seven clinical AI tools by Clinical AI Report across 16 physician reviews
- ✓Enterprise Epic embedding is real and shipping, with Sutter Health, Mount Sinai and Cedars-Sinai live between February and May 2026
Cons
- ✗No differential diagnosis generation and no drug dosing tools — independent reviewers say organisations needing those pair it with a broader clinical decision support platform rather than replacing one
- ✗Benchmark performance is uneven: 100% on USMLE-style questions but a December 2025 preprint reported only 41% for DeepConsult and 34% for Quick Consult on complex subspecialty scenarios, so the headline scores overstate hard-case reliability
- ✗The revenue model puts pharmaceutical and medical-device advertising directly alongside clinical answers, which is a structural conflict of interest buyers have to govern for explicitly
- ✗EHR integration is early — the first enterprise Epic deployments landed in February 2026, so for most users it is still a separate tab rather than an in-workflow tool
- ✗No public SOC 2, HIPAA or ISO 27001 attestation was discoverable, which is a gap for a tool being deployed enterprise-wide inside health systems
- ✗Structural competitive exposure: Epic and Oracle Health are building comparable capability natively, and UpToDate and ClinicalKey are adding AI to corpora they already own, while content licensing costs rise as publishers reprice AI access
Pricing
Verified clinician
$0
- ✓Unlimited Quick Consult and DeepConsult
- ✓Web, iOS and Android
- ✓Requires medical licence verification
- ✓Ad-supported
Health system / enterprise
Contact for pricing
- ✓Enterprise-wide deployment
- ✓Epic EHR embedding
- ✓Deployed at Sutter Health, Mount Sinai and Cedars-Sinai
Free at the point of use for licence-verified clinicians — there is no consumer tier and no self-serve paid plan, so an individual physician adopts it without any procurement step. The business runs on pharmaceutical and medical-device advertising priced at $70 to $1,000+ CPM, far above social-media rates, plus enterprise health-system contracts; Sacra estimates roughly $150M annualised 2025 revenue at about 90% gross margin and around $124 revenue per user. Buyers should price the advertising model as a governance question, not just a commercial one, since the ads sit next to clinical answers.
Security & Compliance
Sources
This page was written from 4 sources, 4 on domains other than openevidence.com.
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