Healthleap, a San Francisco startup that uses artificial intelligence to flag hospitalized patients at risk of malnutrition and other complications, announced Wednesday it closed $38 million in combined funding. The round comprises a $30 million Series A led by Hummingbird Ventures and an $8 million seed co-led by Sequoia Capital and First Round Capital, though the company declined to share its valuation.
The financing marks a notable bet on preventive clinical AI at a time when hospital margins remain under pressure and health systems are scrutinizing return on software investments. Healthleap says it now works with more than 50 hospitals, including a systemwide rollout at Houston Methodist. The software takes a different tack from traditional clinical documentation tools: rather than tidying up records after care is delivered, it screens every adult inpatient each night and surfaces risk scores the following morning.
"Each night, we analyze every adult inpatient's record," CEO and co-founder Josiah Meyer explained in an interview. "Each morning, we write a risk score into the care team's existing workflow."
The platform ingests both structured hospital data (lab results, vital signs, physician orders) and unstructured clinical notes. Its algorithms then generate predictions embedded directly in the electronic health record workflow that clinicians already use. The company launched with malnutrition screening and is expanding to other conditions—including delirium, aspiration pneumonia, congestive heart failure readmissions and pressure injuries—that are undergoing further clinical validation.
A peer-reviewed study published in the journal Applied Clinical Informatics reported that Healthleap's malnutrition model achieved an area under the receiver operating characteristic curve of 0.92 on a patient's first day of admission, rising to 0.95 across the full hospital stay. The analysis drew on more than 166,000 admissions at Cedars-Sinai, though questions about real-world generalizability across different hospital systems remain standard in the field.
Healthleap structures pricing around licensed bed count and signs three-year contracts that include outcome-based components. Meyer claims that every customer has seen at least a fivefold return on investment, with some institutions reporting returns exceeding 20 times annual costs. Such figures, common in vendor marketing, are difficult to verify independently.
The company published a case study with Penn Medicine that projected a $23.8 million annualized financial impact at the Hospital of the University of Pennsylvania. The analysis attributed $6.3 million to higher reimbursement capture and $17.5 million to shorter hospital stays. Healthleap said the deployment saved 8,632 bed-days annually and delivered a 13 percent risk-adjusted reduction in length of stay among patients the AI flagged early.
"The impact has been inspiring, with one hospital seeing 39 percent more malnutrition cases identified and $11 million in incremental revenue," said Alfred Lin, a partner at Sequoia Capital, in a statement.
Still, hospital administrators have learned to approach such projections cautiously. Revenue cycle improvements often depend on complex variables including payer mix, documentation practices and clinical staff adoption—factors that can vary widely between institutions.
Meyer said the new capital will fund hiring across engineering, sales, customer success and product teams. The company's careers page suggests a staff of roughly 25 employees, and Healthleap has reported 13-times revenue growth over the past year, though it did not disclose absolute revenue figures.
The startup was founded in 2022 by siblings Josiah Meyer and Jemima Meyer, a registered dietitian who serves as co-founder and head of research. The company previously raised a $1.1 million pre-seed round led by Fifty Years in early 2022.
Healthleap operates in a growing category of hospital-focused AI tools. It competes with companies like SmarterDx, which concentrates on clinical documentation integrity and revenue cycle optimization, and Pieces, which provides EHR-integrated risk detection and discharge planning summaries. Healthleap positions itself as working "upstream of CDI," a reference to clinical documentation improvement—meaning it attempts to spot clinical risks on day one rather than refine coding after treatment concludes.
Josh Kopelman, co-founder and partner at First Round Capital, said his firm was drawn to what he called the company's "bold vision" to use real-time AI to identify overlooked clinical risk. Whether that vision translates into lasting competitive advantage will depend on clinical validation at scale, something the company is presumably aiming to prove as it grows its hospital footprint.
The healthcare AI sector has attracted significant venture interest over the past two years, though regulatory scrutiny and questions about algorithmic bias continue to shape how quickly such tools gain adoption. For now, Healthleap is betting that hospitals will pay for software that promises to catch problems before they become expensive.
