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Disclosure: I am an independent journalist. I have no financial position in OpenEvidence, Doximity, Teladoc, Waystar, Clarivate, Alphabet (Google), RELX (Elsevier), Wolters Kluwer, Wiley, Epic, Abridge, Hippocratic AI, Anthropic, OpenAI, Baseten, Nvidia, Databricks, Perplexity AI, Hugging Face, SpaceX, Oura, Peloton, Hinge Health, Omada Health, Hims & Hers, Tempus AI, Veeva Systems, IDEXX Laboratories, Verily, Freenome, Commure, Atomic AI, Quadrivia AI, Heidi Health, K Health, UnitedHealth Group, Humana, Johnson & Johnson, Pfizer, Merck, Biogen, Incyte, Goldman Sachs, S&P Global, Softbank, FactSet, Evercore, Altaris, News Corp, The New York Times Company or any other company mentioned in this article or its charts. I have reached out to OpenEvidence and Daniel Nadler for comment multiple times and have received no response. The invitation to an interview on AI Health Uncut and on Digital Health Inside Out stands. Accounts attributed to people familiar with the company come from sources who spoke on condition of anonymity, and were verified against public records where possible. This article is my opinion, based on the sources cited, and is not investment, legal or medical advice.
In Part 1, I looked at the economics of healthtech M&A, with OpenEvidence as the case study: a company that claims $300M in ARR (annual recurring revenue), raised at a $15B valuation in September, and, per Business Insider, “could be open to an M&A deal” (M&A: a merger or acquisition). By any comparable I can find, the business is worth ~$500M or less.
This Part 2 is about the technology. If a buyer pays $15B, what exactly are they buying? A proprietary AI? Proprietary content? Proven accuracy? I looked for all three.
Part 2 is also about the people: how OpenEvidence and its CEO treat critics, and what a buyer would really get in the team.
To everyone who helped with this piece: thank you. It’s because of people like you that I continue doing this work.
A word about how this work gets paid for. Independent investigative journalism comes at a significant cost, both in time and legal risk. That’s why I have launched the AI Health Uncut Sponsorship Program. AI Health Uncut’s subscribers include prominent leaders in healthcare, technology and investment, including household names you would undoubtedly recognize. Sponsorship puts your work in front of all these people, who help shape the industry’s direction, its funding and its adoption of new technologies. Sponsorship does not buy favorable editorial coverage. But I welcome like-minded sponsors who respect my editorial independence and don’t interfere with what I write.
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Four things happened since Part 1:
The Doximity lawsuit is over. On October 16, the day after Part 1 ran, a federal judge in Massachusetts dismissed OpenEvidence’s case against Doximity with prejudice. Each side pays its own legal fees, and the terms were not disclosed. Per Healthcare Dive, OpenEvidence was approaching a deadline to produce internal Slack messages that were allegedly deleted. Probably a coincidence. 😉 Either way, a pending federal lawsuit is exactly the kind of thing that spooks a buyer’s diligence team, and now there isn’t one.
Another big-name announcement. On October 13, OpenEvidence and Johns Hopkins Medicine announced a “landmark collaboration” on medical education and “human-first” AI for patient care. No financial terms, and no research or validation commitments. As I showed in Part 1, OpenEvidence’s announcements have a way of landing right before the money does.
OpenEvidence got its first JAMA paper. On October 15, the day Part 1 ran, JAMA published a study of how clinicians use OpenEvidence: 271M queries from 952,008 clinicians, including 556,200 physicians, between January 2024 and June 2026. Three authors are tied to OpenEvidence, including its chief medical officer, and the company supplied the data. It is a usage study. It counts questions, not correct answers. More in section 5.
The FT profile. On October 20, the Financial Times ran a mostly glowing profile. Per a person close to the company, OpenEvidence booked $100M in “ad buys” for 2025, a metric that includes future advertising commitments, and is on track for $400M to $500M from ads by the end of 2026. Neither number is audited. Even on that projection, $15B is 30x to 37.5x a single year of ad sales. Nadler called OpenEvidence “the first viral consumer internet app in healthcare” and said “the end game is literature-based drug discovery,” worth “orders of magnitude” more than “whatever we could have charged hospitals or advertisers.” So the ad business that supposedly justifies $15B is now the small part of the story.
A note on how this works. Most of my investigations start with a tip from someone like you. I verify it with other witnesses, then add my own “mosaic theory” research on top. Everything stays confidential, always. I have been doing this for 3 years. What follows is a standing public service announcement that I run in every investigation. It is not directed at any company discussed in this piece, and nothing in this article alleges that OpenEvidence or any of its employees or representatives has broken the law or engaged in unethical conduct.
If you see something unethical, or even just weird, anywhere in healthtech, do not stay silent. Tell a newspaper, tell me (DMs, Signal, WhatsApp, whatever you prefer), or, if you believe a law has been broken, tell a law enforcement agency (tips.fbi.gov).
Here is what’s inside:
1. What’s Under the Hood (Still Undisclosed)
2. OpenEvidence Owns None of Its Content. Publishers Can Pull It at Any Time
3. OpenEvidence’s Accuracy: From 100% on the USMLE to 27% on Real-World Cases
4. The Nature Medicine Paper That Sparked OpenEvidence’s PR Meltdown
5. What the New Studies Say About OpenEvidence, and About RAG
6. Patients Not Allowed
7. How OpenEvidence and Its CEO Handle Critics
8. So, Does OpenEvidence Have a Moat?
