Virtual primary care provider K Health announced it secured $50 million in an equity funding round. 

Claure Group led the round with participation from Pablo Legorreta, the founder and CEO of Royalty Pharma. Existing investors Valor Equity Partners, Mangrove Capital Partners and Atreides Management LP also joined the round. 

WHAT IT DOES

K Health is an AI-enabled virtual care provider that offers primary care, urgent care, mental health and medical weight management services. 

The company offers an AI-powered platform aimed at streamlining the provider experience. Patients undergo an assessment via an AI chat. That information is then combined with relevant EMRs and supplies providers with a medical chart with personalized insights. 

New York-based K Health will use the funds to expand its reach within healthcare systems and advance its AI innovations. 

“As I invest in the AI landscape, I have found it incredibly difficult to discover companies making tangible, real-world progress with AI,” Marcelo Claure, founder and CEO of Claure Group, said in a statement. 

“K Health is the first company I’ve seen successfully using AI to impact millions of lives. They are addressing some of healthcare’s greatest challenges by providing accessibility to faster, higher-quality, lower-cost care on a large scale.”

MARKET SNAPSHOT

In 2023, the company raised $59 million in a down round. The investment came from its existing investors and California-based hospital system Cedars Sinai.

It also partnered with Cedars-Sinai to expand the Los Angeles-based health systems’ virtual care options for patients. The organizations collaborated to develop Cedars-Sinai Connect, a virtual healthcare platform powered by K Health’s AI technology. 

Earlier this year, the company announced it entered into a know-how agreement with the Mayo Clinic to develop a clinical AI-enabled solution for cardiac care intended to prevent premature deaths from stroke or heart disease. 

K Health licensed de-identified data from Mayo to refine its AI and create new algorithms aimed at helping physicians predict risk and treatment options by analyzing factors such as medical history, race, age and gender.