OpenEvidence built out a voice AI feature as part of its popular medical search engine that gives physicians a hands-free way to ask questions and get evidence-based answers.
Voice Mode is a native speech-to-speech medical AI interface, and OpenEvidence says it's now the first multimodal medical AI offering for clinical decision support. The feature is live in the OpenEvidence web and mobile apps and is free for all users, according to the company.
Physicians can use the voice mode feature to interact with OpenEvidence when they are moving between rooms, on rounds, walking the corridor outside an OR or charting one-handed during a phone call, executives said.
OpenEvidence has been beta-testing the voice mode feature and the feedback has been "effusively positive," Daniel Nadler, founder and CEO of OpenEvidence, told Fierce Healthcare, giving a first look at the new feature.
"Clinicians have said that Voice Mode allows them to ask questions while commuting or walking around the hospital. Some have even mentioned talking to it in the shower to get high-yield, succinct answers about a case that confounds them," Nadler said.
To use the voice mode feature, a clinician taps the orange waveform icon, asks a question and hears a concise spoken answer drawn from the same sources that power OpenEvidence today, including the New England Journal of Medicine, JAMA, Cochrane, and NCCN guidelines, according to the company.
"There are two sides to building a medical AI—the intelligence and the interface. We've spent years on the intelligence. With Voice Mode, we're advancing the interface to match the everyday reality of practicing medicine," Nadler said.
OpenEvidence developed an AI-powered medical search engine and a generative AI chatbot exclusively for doctors that summarizes and simplifies evidence-based medical information. There are now 860,000 medical licensed-verified U.S. clinicians, including nurses, nurse practitioners and physician assistants, using OpenEvidence, Nadler told Fierce Healthcare, with more than 650,000 licensed-verified U.S. physicians.
OpenEvidence raised a $250 million series D round in January, doubling its valuation to $12 billion. The company's valuation stood at $6 billion in October when it raised $200 million in series C funding—and that was just three months after it raised $210 million in a series B funding round in July.
OpenEvidence has raised roughly $700 million in the past year.
The company has seen rapid growth and now fields more than 1 million clinical questions a day. OpenEvidence is now actively used daily, on average, by more than the majority of physicians in the U.S., spanning more than 10,000 hospitals and medical centers nationwide, according to the company. The company has expanded from clinical search into other clinical workflows, which puts it into more direct competition with players like Wolters Kluwer's UpToDate and Elsevier.
In August, the company rolled out its Visits feature, a clinical AI assistant that transcribes patient visits. The company made an AI-integrated doctor dialer feature more widely available, directly taking on Doximity's core business. In March, it released an AI-powered medical coding feature that provides automatic Current Procedural Terminology (CPT) code suggestions and evaluation and management (E/M) level recommendations.
The new voice mode feature opens up its capabilities to clinicians who are not at a screen. Voice answers are shorter and shaped for listening; the references and the full written form remain in the conversation, so the verification standard is the same as for written responses, executives said.
Every spoken answer comes with the written transcript and underlying references in the same conversation. Clinicians can interrupt mid-answer to redirect or refine the question. In noisy environments, a tap mutes the microphone until they are ready to speak again. For physicians who want voice input without a spoken response, a separate microphone icon dictates the question as text into a standard OpenEvidence search.
“When I’m in the ED, I’m never at a workstation when I actually need an answer. I’m gloved, gowned, on the phone or in between patients. Voice Mode gives me the answers I need in those in-between moments," said Ania Bilski, M.D., vice president of clinical AI at OpenEvidence and a practicing emergency medicine physician at UCSF and Kaiser Permanente.
OpenEvidence's enterprise ambitions
The company gained traction in the market as a free tool for clinicians, but OpenEvidence is now setting its sights on growing its footprint with hospitals and health systems. In the past three months, the company has announced collaborations with Mount Sinai and Sutter Health to integrate its AI-based medical search and decision-support platform into an organizations' electronic health record systems.
This week, Cedars-Sinai joined that list, providing clinicians with enterprise access to OpenEvidence to combine medical evidence with relevant information from a patient’s electronic health record. Through the partnership, Cedars-Sinai physicians, nurses, pharmacists and therapists can ask clinical questions and retrieve medical literature that is relevant to an individual patient’s health profile, the health system said.
Sutter Health, Mount Sinai and Cedars-Sinai are currently using OpenEvidence's ad-supported model.
"Advertising has long been part of how clinicians access medical research through journals, and this represents a similar model in a digital format—our priority is ensuring the experience maintains clinical integrity and supports high-quality care," Shaun Miller, M.D., chief health informatics officer at Cedars-Sinai, told Fierce Healthcare.
Nadler said an enterprise model is in the works.
"We are pioneering a non-ad-supported, standard AI enterprise model, similar to Anthropic's business model, for large systems like Mount Sinai or Cedars-Sinai who want that option and where there is significant opportunity for enterprise-level customization and value-add beyond the core free-for-physicians OpenEvidence product," he said.
Miller said OpenEvidence stood out for its "AI-native approach to synthesizing clinical evidence directly within the workflow."
"We also heard strong clinician preference for its usability and saw an opportunity to partner with an innovative company advancing how evidence can be delivered efficiently in a safe and secure way," Miller said.
"We opted for an enterprise-wide rollout to ensure equitable access, accelerate adoption, and gather broad, early feedback across specialties and various clinical roles. We’ll evaluate clinician engagement, workflow impact, and how effectively these tools support clinical decision-making," Miller said.
The deployment of OpenEvidence enterprise-wide ties into Cedars-Sinai's broader AI strategy, Miller noted. "This reflects our strategy to embed AI directly into the workflow while partnering with leading innovators to scale meaningful impact. The goal is to integrate AI seamlessly into how clinicians deliver high-quality care safely," he said.
Health systems are seeing strong demand from clinicians for access to OpenEvidence within the EHR, organization leaders said.
“Clinicians, particularly our doctors, were asking for it,” Nicholas Gavin, M.D., vice president and chief clinical innovation officer of the Mount Sinai Health System, told Fierce Healthcare. Mount Sinai announced its collaboration with OpenEvidence in March.
“Every health system has a few senior clinicians who we all turn to for challenging cases—the Dr. House’s of the world. One of the senior physicians at Mount Sinai came to me, as we were working on this partnership. I didn’t know if he was a supporter or a detractor, so I led with, ‘What do you think? When should we get this done?’ His response was ‘Yesterday.’ Very few technological tools get that kind of response from clinicians,” Gavin said.
Often, health systems will roll out new technology through pilot projects before scaling more broadly, but the three health systems went out of the gate with enterprise-wide deployments.
“We are convinced that this tool can transform care by providing information and insights at the point of care. We do pilots when necessary, always with the goal of scaling. This was not one of those situations. However, we will be conducting ongoing usability and evaluations,” Gavin said.
Providing clinicians with AI-powered medical evidence at the point of care reflects Mount Sinai’s broader vision to responsibly scale AI across the health system, Mount Sinai executives said.
“One of our core objectives is driving toward precision healthcare delivery, and AI and digital tools are essential for this,” Gavin said. “This is one tool on the journey to that destination. Our eventual goal is real-time integration of patient data with the latest evidence to provide precision insights and guidance to our clinical team, who are trying to do so much at any given time. No human, by themselves, can achieve the standards that we hold ourselves to for every single patient encounter. This helps us get closer to the ideal state.”