Nurses, Meet the “ChatGPT for Clinicians” That Just Raised $200 Million

- OpenEvidence is an AI-driven clinical assistant built by Harvard/MIT-trained researchers to deliver cited, evidence-based answers from trusted medical journals like NEJM and JAMA.
- The startup’s new $200 million funding round at a $6 billion valuation signals strong investor belief in AI built specifically for clinicians.
- For nurses, especially those in advanced practice or leadership roles, the platform could streamline evidence searches, boost clinical confidence, and support faster, guideline-aligned decisions.

Image source: OpenEvidence
OpenEvidence, often described as “ChatGPT for clinicians,” has secured a new $200 million round at a $6 billion valuation, according to TechCrunch and The New York Times. Founded in 2022, the Boston-based startup is rapidly becoming one of the most prominent AI tools used by clinicians, with its usage nearly doubling to 15 million monthly consultations since July.
This new funding round isn’t its first this year, having previously secured $75 million at a $1 billion valuation in February, and $210 million at a $3.5 billion valuation in July.
What is OpenEvidence?
OpenEvidence is an AI-driven clinical assistant available for verified clinicians with NPIs, drawing solely from trusted sources like the New England Journal of Medicine and JAMA. Its mission is to “organize and expand the world's collective medical knowledge.”
Designed by Harvard and MIT researchers, the tool aims to make complex medical literature instantly accessible at the bedside or point-of-care. Unlike general chatbots, it cites every answer so clinicians can trace insights back to peer-reviewed evidence.
The platform is currently free for verified clinicians, supported by an ad-based model that has helped it scale across more than 10,000 hospitals and medical centers. A recent physician survey shared via Sermo found that 21% of users describe it as a “useful tool for supporting decisions,” while 24% said it saves time, streamlining “clinical decisions with fast, evidence-based answers.”
Source: Apple App Store
Why It Matters for Nurses
For nurses—especially those in advanced practice, critical care, or outpatient leadership—OpenEvidence could serve as a time-saver and a clinical confidence booster.
The tool can generate quick, cited summaries to answer questions such as “What are best practices for wound care in diabetic patients?” or “Which antihypertensive agents are safest postpartum?” Without needing to sift through multiple resource databases, nurses can get reliable, referenced guidance aligned with current guidelines.
This kind of streamlined, evidence-backed support could be especially valuable to nurse practitioners managing complex conditions or bedside RNs developing care plans. As one pediatric specialist quoted by Sermo put it, “Evidence-based Medicine is a tenet of our clinical acumen, and OpenEvidence AI can make this accessible on the wards and at the bedside.”
Competition in Clinical AI
OpenEvidence isn’t alone in this rapidly growing category of healthcare-focused AI. Competitors include:
- Pathway: which provides concise guideline summaries and point-of-care algorithms for healthcare professionals.
- Dr.Oracle: an evidence-based AI companion for physicians that references clinical guidelines and supports medical exam prep.
- Medwise AI: a UK-based clinical question-answering platform offering a customizable search interface for clinicians.
- Abridge and Doximity: both working to integrate AI directly into clinician workflows through EHR connectivity and voice documentation.
The Takeaway
With major backers like Google Ventures, Sequoia Capital, and Blackstone, OpenEvidence’s trajectory signals that AI designed specifically for clinicians is where investors see real promise.
For nurses, it offers a glimpse of an evidence-driven future where care decisions can be supported instantly, transparently, and safely from trusted medical literature.
As the company secures a ~$6 billion valuation and scales further, it’s worth keeping an eye on how access expands, how nursing-specific use cases develop and how institutions embed such tools in inter-professional workflows.
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