OpenEvidence, the young American startup specializing in artificial intelligence applied to the medical sector, is experiencing spectacular growth. In just three months, its valuation has doubled, now reaching 12 billion dollars, following a record fundraising of 250 million dollars during a Series D round. This success sheds new light on the challenges related to the integration of AI in healthcare, a sector undergoing rapid digital transformation. OpenEvidence’s platform, adopted by more than 40% of American doctors, is establishing itself as an essential reference across more than 10,000 hospitals and care centers. This pioneering startup is committed to providing practitioners with tools that are both reliable, secure, and performant, based on artificial intelligence specialized in medicine.
In 2026, faced with the multiplication of information sources and the growing complexity of medical data, OpenEvidence has positioned itself as a key player to help healthcare professionals quickly access validated knowledge. Through an advanced medical search engine and a dedicated generative chatbot, the startup is revolutionizing the way doctors interact with scientific research. Its ambition to build a “medical super-intelligence” capable of solving complex cases demonstrates a deep commitment to more precise, faster, and safer medicine, and reveals an ambitious vision that far exceeds the usual promises of AI in healthcare.
- 1 OpenEvidence: major fundraising and doubling of valuation in record time
- 2 A medical AI platform adopted by 40% of American doctors
- 3 The medical search engine and generative chatbot: revolutionary tools for healthcare professionals
- 4 Strategic partnerships with leading medical institutions
- 5 “Medical super-intelligence”: the future of multi-agent AI coordination in healthcare
- 6 Secure and HIPAA-compliant use: innovation in medical communication
- 7 A competitive market where OpenEvidence stands out thanks to its health specialization
- 8 Development prospects for faster, more precise, and safer medicine
OpenEvidence: major fundraising and doubling of valuation in record time
OpenEvidence’s 250 million dollar fundraising is much more than a simple financial operation. It symbolizes the confidence investors place in the disruptive potential of this startup, but also in the future of artificial intelligence technologies within modern medicine. This amount, raised during a Series D round co-led by Thrive Capital and DST Global, attaches OpenEvidence to an elite group of healthtech companies whose valuations now exceed several billion.
It is remarkable that the valuation doubled in just three months, a strong indicator of the rapid growth and commercial momentum displayed by this young company. It also attests to increased market demand for specialized AI solutions capable of providing tangible added value to the daily work of healthcare professionals. In November 2025, the startup was valued at 6 billion dollars; today it doubles this figure to reach 12 billion, demonstrating massive financial actors’ confidence in its business model and technological vision.
More concretely, this massive funding will allow OpenEvidence to accelerate its investments in research and development, with a clear focus on the sophistication of its AI models. The doubling of valuation is a direct reflection of these ambitions, as well as the consolidation of its place in a market where competition is intensifying between startups and tech giants interested in the digital transformation of the medical field.
A medical AI platform adopted by 40% of American doctors
OpenEvidence has quickly established itself as a trusted technology in the American medical world. In 2025, more than four out of ten doctors use its tools daily, a massive adoption that illustrates how much the AI integrated into the platform responds to a pressing need for efficiency and precision in clinical practice.
This massive adoption follows the gradual deployment of the platform across more than 10,000 hospitals and medical centers throughout the United States. This widespread implantation fosters the transformation of medical practices by enabling professionals to access, in record time, validated, synthesized information that is relevantly addressed to their clinical queries. For example, an emergency team in a New York hospital can instantly consult the latest recommendations from a scientific consensus, without having to sift through dozens of publications.
Furthermore, this rapid breakthrough reflects a cultural shift within hospitals and clinics, where technology is no longer confined to an assistant role but becomes a full-fledged decision-making partner. OpenEvidence thus contributes to reducing medical errors, saving precious time during decision-making, and improving interdisciplinary coordination based on up-to-date and rigorously validated data.
This adoption also addresses frequent criticisms directed at other technologies: unlike some medical chatbots that provide generic or unverified answers, OpenEvidence relies exclusively on validated sources and recognized institutions, ensuring permanent quality control.
The medical search engine and generative chatbot: revolutionary tools for healthcare professionals
At the heart of OpenEvidence’s innovation lies the unique combination of a medical search engine powered by artificial intelligence and a chatbot specifically designed for doctors’ needs. This approach allows dynamic interaction between the user and a colossal, synthesized, and structured knowledge base.
The search engine leverages the latest advances in cognitive robotics and natural language processing to analyze and deliver results derived from up-to-date scientific articles, clinical studies, guidelines, and institutional recommendations. For example, when a practitioner searches for data on innovative treatments for type 2 diabetes, the platform offers a clear, comparative, and updated synthesis, thus avoiding dispersion and time loss related to navigating between different sources.
On the other hand, the generative chatbot provides a conversational dimension, capable of understanding complex questions, clarifying ambiguities, and guiding doctors in their choices. This interaction goes far beyond simple databases, as it relies on cutting-edge algorithms combined with strict ethical rules to produce reliable, explicit, and contextualized answers.
These two combined tools structure clinical practice by facilitating access to validated scientific data in real time. It is no longer just about accessing information but transforming it into operational knowledge with added value for patient care.
Strategic partnerships with leading medical institutions
OpenEvidence’s success also relies on its network of solid collaborations with prestigious medical institutions. This approach aims to guarantee the reliability and scientific quality of the data exploited by the platform. Key partners include the American Medical Association (AMA), the New England Journal of Medicine (NEJM), and the Journal of the American Medical Association (JAMA), as well as academies such as the American Academy of Family Physicians and the American College of Emergency Physicians.
These collaborations allow access to exclusive content, often unavailable to the general public or uncertified tools. They also ensure a continuous process of updating and quality control of integrated algorithms, thus reinforcing the startup’s credibility with practitioners and decision-makers.
For example, recommendations and updates published by the AMA or the NEJM are quickly integrated into OpenEvidence’s search engine, which contextualizes and simplifies them without altering scientific rigor. This prevents the pitfall of erroneous or outdated information and increases end-users’ trust.
Furthermore, the startup strictly respects copyright laws by ensuring that all exploited content is licensed or obtained through formal agreements. This attention to ethics in data processing strengthens the legal security of the proposed solution.
“Medical super-intelligence”: the future of multi-agent AI coordination in healthcare
One of OpenEvidence’s most ambitious objectives is to develop a “medical super-intelligence,” a sophisticated system that coordinates several artificial intelligence models specialized in different clinical sub-domains. This multi-agent approach replicates the dynamics of multidisciplinary teams found in large hospitals, where each expert focuses on a specific area.
Specifically, a central system directs each medical request to the most suitable model, leveraging fine orchestration to quickly and accurately solve complex cases. This artificial collective intelligence model surpasses the capacities of a single generic AI by combining the expertise of several specialized intelligences.
An example of use would be an emergency situation where a patient’s symptoms require a cross-diagnosis between cardiology, neurology, and immunology. OpenEvidence’s system analyzes the request, distributes the work among specialized AI models, and presents the doctor with a report integrating multiple expertises within seconds.
This strategic innovation sets OpenEvidence apart from competitors who often offer more general tools or those not focused on complex clinical cases. The promise is thus to improve the speed and safety of diagnoses in a context where every minute counts for patients’ lives.
Secure and HIPAA-compliant use: innovation in medical communication
In December 2025, OpenEvidence launched a unique feature: secure automatic numbering, which facilitates communication among healthcare professionals while strictly complying with the US HIPAA (Health Insurance Portability and Accountability Act) law. This solution was designed to protect confidential exchanges, a major issue in a sector where data protection is crucial.
This novelty allows doctors to contact their peers without exposing their information to unauthorized third parties or risking violation of privacy regulations. For example, an emergency doctor can quickly reach a specialist via this secure channel to validate a diagnosis or request a complementary opinion.
This feature strengthens OpenEvidence’s position as a complete and integrated solution in the daily lives of healthcare professionals, combining artificial intelligence, data security, and compliance with regulatory standards.
| Feature | Description | Impact on medical practice |
|---|---|---|
| AI Search Engine | Fast search and synthesis of validated medical journal information | Time savings and reliable access to quality sources |
| Specialized generative chatbot | Interactive response to complex clinical questions | Improvement of medical decision-making |
| Multi-agent super-intelligence | Coordination of several specialized AI models for managing complex cases | Rapid and precise diagnosis, safer for the patient |
| Secure automatic numbering | HIPAA-compliant communication between healthcare professionals | Securing exchanges and respecting sensitive data |
A competitive market where OpenEvidence stands out thanks to its health specialization
The sector of artificial intelligence applied to health is now a major strategic challenge for actors from both tech and medical fields. OpenAI, Anthropic, and other AI giants are increasingly entering this domain, often with generalist solutions intended for a broad audience, researchers or clinicians.
However, Daniel Nadler, founder and CEO of OpenEvidence, states that exclusive focus on the medical market provides a decisive competitive advantage. “We believe that in 2026, betting on specialized health is the key to real impact,” he explains. This focus allows the company to refine its models, improve data quality, and adapt its services more quickly to specific clinical needs.
This strategy has already enabled OpenEvidence to cross an important financial threshold: the startup has raised more than 700 million dollars to date and now exceeds 100 million dollars in annual revenue, mainly generated through service subscriptions by medical institutions.
Development prospects for faster, more precise, and safer medicine
OpenEvidence’s ambition goes beyond merely providing tools. The startup is committed to transforming how doctors access and use medical knowledge. This commitment relies on the continuous development of specialized models that support faster, more precise, and above all, safer medicine for patients.
For example, the integration of modules dedicated to emergencies, pediatrics, or cardiology enables specialized support capable of adapting to particular clinical contexts. This gradual evolution towards a multidisciplinary digital team embodies a vision where technology complements, without ever replacing, human expertise.
This dynamic is essential in a medical landscape where the volume of information keeps growing, making the use of reliable and efficient decision support tools indispensable. Ultimately, OpenEvidence aspires to accompany a systemic transformation of medical practices, in which AI will be a central ally to improve patients’ quality of life and therapeutic outcomes.