AI startup OpenEvidence secures Sequoia funding, $1 billion valuation

AI startup OpenEvidence is raising a fresh round of capital from Sequoia to scale its chatbot for doctors. 

The brand new $75 million money injection, which has not been previously reported, values OpenEvidence at $1 billion, the 2 firms told CNBC. 

OpenEvidence, based in Cambridge, Massachusetts, was founded by Daniel Nadler. He previously built Kensho Technologies, a Wall Street-focused artificial intelligence firm that sold to Standard & Poor’s for $700 million in 2018. 

Nadler’s newest AI enterprise is a chatbot for physicians that helps them make higher decisions at the purpose of care. The corporate claims it’s already getting used by 1 / 4 of doctors within the U.S. 

Following his sale of Kensho, Nadler self-funded OpenEvidence in 2021 before raising a family and friends round in 2023. The funding from Sequoia represents the primary round led by an institutional investor and brings the corporate’s total amount raised to greater than $100 million.

The corporate may also use the funding to forge strategic content partnerships, OpenEvidence said. Along with the funding, OpenEvidence announced that The Recent England Journal of Medicine has change into a content partner, meaning clinicians using OpenEvidence can profit from content sourced from NEJM Group journals.

The founder describes OpenEvidence as an AI copilot. While the experience may feel much like ChatGPT, OpenEvidence is a “very different organism” as a consequence of the information it was trained on, Nadler said. 

“Trust matters in medicine, and the indisputable fact that it’s trained on The Recent England Journal of Medicine, the indisputable fact that it’s built from the bottom up for doctors — the result’s a black-and-white difference when it comes to accuracy,” Nadler told CNBC.

The corporate has licensing agreements with peer-reviewed medical journals, and OpenEvidence’s model was not connected to the general public web while trained, Nadler said. Using tailored data helped OpenEvidence avoid the pitfalls of “hallucination,” which is a phenomenon where AI will generate inaccurate, sometimes nonsensical answers to a question.

OpenEvidence offers its chatbot totally free and makes money off of promoting. The product has grown organically due to word of mouth between doctors, Nadler said.

“Doctors work very close quarters with each other, especially on the ground in hospitals,” he said. “When one doctor pulls out their iPhone and appears at something, other doctors can see that. Their natural query is, ‘What’s that?'” 

That level of organic growth was an alluring factor for Sequoia partner Pat Grady, who led the firm’s investment. Sequoia is best known for early investments in Nvidia, Apple, YouTube, Stripe, SpaceX and Airbnb.

“It is a consumer web company masquerading as a health-care business,” Grady told CNBC, saying OpenEvidence is straightforward for doctors to adopt. “Once they have a pair of excellent experiences with it, it sticks. There aren’t a variety of products in health care that get adopted the way in which that a consumer web company might.”

OpenEvidence is the most recent in a flood of Silicon Valley artificial intelligence deals. 

The booming sector accounted for 1 in 4 enterprise dollars raised by startups last yr, in response to CB Insights. Health care has stood out as a high-potential area for the applying of AI. Investors and founders have seen the technology’s ability to sift through large amounts of knowledge, and its potential to rework every thing from drug discovery to medical imaging.

“There are a variety of great ideas in health care, however it is such a posh system,” Grady said. “It’s really hard to chop through layer upon layer upon layer.” 

While AI has the potential for health-care breakthroughs, there are also worries concerning the risks. Industry leaders have voiced concern a couple of “doomsday” scenario where the technology results in a catastrophic consequence for humanity, and on the smaller scale, others worry about job displacement.

OpenEvidence’s Nadler said he thinks the health-care use cases are the antidote, and represent the upside potential of AI. He highlighted doctor burnout and projections of an almost 100,000 physician shortfall by the tip of the last decade. 

“There’s this big query that is on everybody’s mind straight away, is AI actually going to be good for humanity or not?” Nadler said. “I feel it’s, inarguably, going to be good.”