Healthleap raises $38M for AI that finds undiagnosed conditions in hospital patients

Malnutrition is one of the most common conditions hiding in plain sight inside U.S. hospitals. Up to half of hospitalized patients may be at risk, according to Healthleap, but fewer than 9% receive a diagnosis. That gap can mean longer hospital stays, worse patient outcomes, and millions of dollars in added costs.

Healthleap thinks software can catch what busy clinical teams miss.

The healthcare AI startup has raised $38 million in combined seed and Series A funding to expand a platform that reads patient records daily and flags people who may be at risk for undetected conditions. The financing includes an $8 million seed round co-led by Sequoia Capital and First Round Capital and a $30 million Series A led by Hummingbird Ventures.

Healthleap’s story started with malnutrition. Co-founder Jemima Meyer was working as a clinical dietitian when she built an early tool to help dietitians find patients who needed attention sooner. She later teamed up with her brother, Josiah Meyer, and the pair founded Healthleap in South Africa in 2022.

What began as a nutrition tool has since become a broader clinical AI platform. Healthleap now sits on top of hospital electronic health record systems, analyzing notes, lab results, vital signs, medications, diagnoses and other patient data for signs that someone may need a closer look.

The software does not diagnose patients. It assigns risk scores and routes them into existing hospital workflows so clinicians can decide what happens next.

From malnutrition screening to a broader hospital AI layer

Healthleap’s pitch is gaining attention partly because the company can point to measurable results.

At the Hospital of the University of Pennsylvania, Healthleap says its malnutrition program generated $23.8 million in annualized financial impact. That figure included $6.3 million in additional reimbursement and an estimated $17.5 million tied to shorter hospital stays, representing 8,632 annualized bed-days saved. Penn Medicine’s Strategic Decision Support team reviewed the analysis, Healthleap said.

At Cedars-Sinai, the company reports a 39% increase in malnutrition diagnoses with the same staffing levels and $11 million in annual financial impact.

Announcing the funding in a LinkedIn post, Josiah said:

“Somewhere right now, a patient is getting sicker from something that was treatable all along. HealthLeap AI finds these patients. We use existing signals in the patient record to screen every inpatient every day and flag those at high risk, so care teams can act and care for those patients. We started with malnutrition. My sister and co-founder, Jemima, worked as a clinical dietitian and watched patients get found too late.”

Healthleap also has clinical research behind its core malnutrition model. A peer-reviewed study published in *Applied Clinical Informatics* evaluated more than 166,000 hospital admissions over 3.75 years. The company says the system showed 88% higher sensitivity than a modified Malnutrition Screening Tool and identified patients an average of four days before the first dietitian documentation.

The startup has grown from three hospital partners to more than 50 over the past year, with customers including Penn Medicine, Cedars-Sinai, Houston Methodist, Emory Healthcare and Intermountain. CEO Josiah Meyer told TechCrunch that revenue increased more than tenfold during the same period.

“Every week, millions of patients leave hospitals with unresolved health conditions that will erode their health and cost up to 10x more to treat later,” Meyer said. “Finding them now is prevention, and it’s a win for everyone. Patients get treated before they get sicker. Hospitals shorten stays and are paid for the care they deliver. Payers avoid the much higher cost of complications down the road. Our goal is to improve care and save lives by catching these conditions early.”

Malnutrition is becoming the starting point, not the entire product. Healthleap is developing screening programs for delirium, aspiration pneumonia, pressure injuries, and congestive heart failure readmission risk. Meyer says the longer-term goal is to cover more than 40 major conditions and eventually extend the system beyond hospitals into outpatient and home care.

The new funding will go into engineering, product development, sales, and customer success.

Healthleap bets that one of AI’s most valuable roles in hospitals may be surprisingly straightforward: continuously reading records humans rarely have time to reread, then pointing clinicians to the patients most likely to have been overlooked.

Healthleap Team (Image credit: Healthleap)