OpenEvidence

OpenEvidence is an artificial intelligence-powered medical information and clinical decision-support platform developed by OpenEvidence Inc. It is designed primarily for physicians and other verified healthcare professionals who need to find, understand, and evaluate medical evidence while making clinical decisions. The platform allows users to ask medical questions in natural language and receive structured answers supported by citations from peer-reviewed research, clinical guidelines, and trusted medical publications. Its main objective is to make reliable medical knowledge easier to access and apply in clinical practice.

OpenEvidence was founded in 2022 by Daniel Nadler and Zachary Ziegler, while its medical search platform was launched in 2023. The company developed the service to address the challenge of navigating an expanding body of medical research. Healthcare professionals regularly need to consult journal articles, systematic reviews, treatment guidelines, and other clinical resources. Finding relevant information across these publications can take considerable time, particularly when a question requires comparing evidence from several sources. OpenEvidence uses AI-powered search and summarization to make this research process more accessible.

The platform works as a conversational medical search engine. Instead of relying exclusively on traditional keyword searches, clinicians can describe a medical question in ordinary language. OpenEvidence interprets the question, searches relevant medical information, and generates an answer that brings together findings from the available literature. Users can ask follow-up questions to explore a topic in greater detail, clarify an earlier response, or examine different aspects of a clinical issue. This conversational approach helps users investigate complex subjects without repeatedly starting a new search.

A major part of OpenEvidence’s approach is its emphasis on cited medical information. Answers include references that allow clinicians to identify the publications supporting the generated response. This is important because medical information must be evaluated in context, and a summary alone may not communicate the limitations of a study or the strength of its findings. By providing references alongside its answers, OpenEvidence gives users a way to examine the underlying literature rather than relying entirely on an AI-generated explanation.

The platform draws on a substantial collection of medical publications and trusted information sources. Its content partnerships include The New England Journal of Medicine (NEJM), the Journal of the American Medical Association (JAMA) and the JAMA Network, Nature and the Nature Portfolio, Wiley, Sage, and the Cochrane Library. It also incorporates information from professional medical organizations and clinical guideline providers. Its collaboration with the National Comprehensive Cancer Network (NCCN), for example, makes selected oncology guidelines and treatment algorithms available through the platform. These relationships help provide access to established medical resources across different specialties.

OpenEvidence also includes information from organizations such as the American Academy of Family Physicians, American College of Cardiology, American Diabetes Association, American Academy of Pediatrics, American College of Obstetricians and Gynecologists, and American College of Emergency Physicians. These resources are relevant to a broad range of clinical questions, including diagnosis, treatment recommendations, disease management, and preventive care. The platform’s partnerships with medical publishers and professional societies are an important part of its identity because they distinguish its research-focused approach from general-purpose AI chatbots that may draw on less specialized information.

One of its notable features is EvidenceGrade, which evaluates and presents information about the quality of the published evidence supporting an answer. Medical studies do not all provide the same level of certainty. Randomized controlled trials, systematic reviews, observational studies, and individual case reports have different strengths and limitations. EvidenceGrade is intended to help clinicians understand the strength of the research behind an answer and consider how confidently the findings may apply to a particular clinical situation. It builds on principles associated with established evidence-assessment approaches, including the GRADE framework. This feature adds an additional layer of context to AI-generated medical summaries.

OpenEvidence expanded its underlying AI capabilities in September 2026 with the introduction of the OpenEvidence model family. The production models include Osler, Sackett, and Snow. Osler is designed for faster responses during clinical encounters, while Sackett provides a more detailed research approach for questions that require closer examination of the available evidence. Snow is designed for deeper investigations that examine medical literature across multiple research paths before producing a report. These models allow clinicians to select an approach that better matches the time and depth required by a question. The company also introduced Darwin as a research-preview model available through a restricted application process. Darwin is not presented as a standard model available to every user.

In addition to medical search, OpenEvidence has developed tools that support other parts of the clinical workflow. Visits provides ambient documentation capabilities intended to help clinicians create medical notes from patient encounters. This can reduce the amount of manual documentation required during a consultation, although clinicians remain responsible for reviewing and correcting the resulting record. Coding Intelligence extends this workflow by generating suggested ICD-10 diagnoses, evaluation and management recommendations, supporting medical decision-making rationale, and CPT procedure-code suggestions based on clinical documentation. These features are designed to help healthcare professionals manage documentation and billing-related tasks more efficiently.

The platform also includes Voice Mode, which allows clinicians to interact with OpenEvidence through spoken questions and receive information without relying entirely on typed prompts. The Doctor Dialer supports secure patient-call workflows, while Patient Take-Homes allows clinicians to turn selected answers into educational materials for patients. Healthcare professionals can adjust the language and level of detail of these materials before sharing them. Patients receiving a Take-Home are given access to the information selected by their clinician rather than an unrestricted version of the medical question-and-answer service.

OpenEvidence has also expanded into medical education through OpenEvidence Learn, introduced in November 2026. Learn is designed to support medical students, trainees, and practicing clinicians through personalized educational resources. Its available tools include Test Prep, which provides board-style practice questions for medical school, residency, fellowship, and professional examinations; Preceptor, which offers case-based learning and simulated clinical scenarios; and Flashcards, which help users review medical topics and reinforce information over time. The platform also includes continuing medical education features. These additions extend OpenEvidence beyond point-of-care research into professional learning and ongoing medical education.

For healthcare organizations, OpenEvidence Enterprise provides an institutional deployment option. It is designed to make the platform available within an organization’s existing clinical environment through features such as institutional single sign-on, governed access, and electronic health record integration. Depending on the deployment, clinicians may be able to launch OpenEvidence directly from an EHR rather than signing in separately. Enterprise arrangements also provide organizational controls for handling protected health information, retention policies, and access management. OpenEvidence has announced integrations and collaborations with healthcare systems including Mount Sinai Health System, Cedars-Sinai, Memorial Sloan Kettering Cancer Center, Northwestern Medicine, and NYU Langone Health.

Security and privacy are important considerations because clinical workflows may involve sensitive patient information. OpenEvidence identifies HIPAA compliance and SOC 2 Type II as part of its security and compliance program. Its enterprise offering describes institutional agreements, data controls, and arrangements for handling protected health information. Healthcare organizations should still review the relevant agreements, configuration options, and security documentation before introducing the platform into their clinical workflows.

OpenEvidence is available through its website and mobile applications for iOS and Android, with a desktop application also offered. The desktop version provides quick access through a global keyboard shortcut, allowing users to bring up the service without repeatedly opening a browser tab. The main platform is intended for verified healthcare professionals, and access requirements vary according to the user’s professional status and location. Its free access model is specifically advertised for verified U.S. clinicians, so availability should not be assumed to be the same in every country.

The platform’s main audience includes physicians, medical residents, healthcare practitioners, and other eligible clinical professionals who need a convenient way to research medical questions. Its educational tools also serve medical trainees and clinicians pursuing continuing professional development. Healthcare organizations may find the enterprise offering relevant when they want to make evidence-based information available within existing clinical systems.

OpenEvidence is not a replacement for professional medical judgment, clinical training, or established patient-care procedures. AI-generated answers may contain errors, omit important context, or summarize research in ways that require further examination. Even when references are supplied, users should review the original publications and relevant guidelines before relying on information in a clinical decision. The platform is best understood as a research and decision-support resource that helps qualified professionals locate and evaluate information, rather than an independent authority that makes clinical decisions.

Overall, OpenEvidence combines conversational medical search, cited research summaries, evidence-quality assessment, clinical workflow tools, and medical education features in one platform. Its partnerships with major medical publishers and professional organizations provide a substantial foundation for its research capabilities. Features such as EvidenceGrade, the Osler, Sackett, and Snow models, Visits, Coding Intelligence, and OpenEvidence Learn broaden its usefulness beyond basic question answering. Although its professional verification requirements and geographic availability limit access for some users, OpenEvidence has developed into a specialized medical AI platform for clinicians and healthcare institutions that need faster access to research-based information.

Pricing

OpenEvidence offers its core medical information platform free to verified U.S. healthcare professionals. The company does not publish a conventional monthly or annual subscription price for individual clinicians.

• Individual clinician access – Free: Verified eligible U.S. healthcare professionals can access the core platform without a subscription fee.
• OpenEvidence model family – Free for verified clinicians: Osler, Sackett, and Snow are included in the clinician platform.
• OpenEvidence Learn – Free: The medical education platform is available to OpenEvidence users without an additional published subscription charge.
• OpenEvidence Enterprise – Free to eligible organizations: The company advertises institutional deployment at no cost, subject to eligibility and an organizational agreement.
• Darwin – Research preview: Access is restricted and available through an application process rather than a standard public subscription.

Review

OpenEvidence is a specialized medical AI platform with a strong focus on evidence-based information. Its conversational search experience makes it easier for clinicians to investigate medical questions and obtain summaries supported by references. Rather than presenting an answer without context, the platform provides citations that allow users to examine the research behind its responses. Its partnerships with established medical publishers and professional organizations also strengthen its position as a medical research resource.

EvidenceGrade is a valuable feature because it helps users consider the quality of the evidence supporting an answer. The availability of different models, including Osler, Sackett, and Snow, also gives clinicians options for questions requiring different levels of research depth. The addition of Visits and Coding Intelligence broadens the platform’s usefulness by supporting documentation and coding-related tasks, while OpenEvidence Learn introduces resources for medical education and continuing professional development.

Another advantage is its availability across web, mobile, and desktop environments. Healthcare organizations can also explore enterprise deployments that connect the platform with existing clinical systems. Its HIPAA and SOC 2 Type II security program is relevant to institutions evaluating software for healthcare workflows.

However, OpenEvidence has limitations. Its free individual access is primarily intended for verified U.S. healthcare professionals, which means availability may be restricted for people outside the supported regions or without the required professional credentials. It is also not a general-purpose research assistant for every type of user. Its medical focus and professional verification requirements make it more specialized than ordinary AI chatbots.

Accuracy is another important consideration. Cited answers can make medical research easier to review, but citations do not guarantee that every generated statement is correct or that the selected evidence is appropriate for every patient. Users must assess the original research, consider patient-specific circumstances, and apply professional judgment. The platform should not be treated as a substitute for clinical expertise or independent verification.

Overall, OpenEvidence is a strong medical information and clinical decision-support platform for its intended professional audience. Its combination of cited medical search, evidence assessment, workflow support, and educational features makes it a useful resource for eligible clinicians. Its geographic and professional access restrictions, together with the need to independently evaluate AI-generated answers, are important limitations to consider.