A healthcare artificial intelligence startup that analyzes patient records to flag individuals who may be suffering from undiagnosed conditions has closed a combined $38 million in seed and Series A funding. The company, Healthleap, secured an $8 million seed round co-led by Sequoia Capital and First Round Capital, followed by a $30 million Series A led by Hummingbird Ventures. Healthleap has not disclosed a valuation in connection with either round.

The startup was founded in South Africa in 2022 by siblings Jemima and Josiah Meyer. In its earliest form, the company offered a clinical nutrition tool that Jemima had originally developed for use by dietitians. Over time, the team shifted direction and built a broader platform designed to identify hospitalized patients who may be experiencing conditions such as malnutrition or delirium - conditions that frequently go undetected until they have already affected a patient's recovery. Josiah Meyer serves as CEO and co-founder.

Reading Between the Lines of Patient Records

At the heart of Healthleap's approach is the recognition that patient charts contain two distinct types of information. Structured data fields capture things like laboratory results, body weight measurements, and vital signs. But clinicians' written notes often contain equally important clinical signals - references to a patient's poor appetite, recent weight loss, muscle deterioration, or difficulty swallowing - that don't fit neatly into structured formats.

"A patient's chart holds two kinds of data. Labs, weights, and vital signs sit in structured fields, but the most telling signs sit in clinicians' written notes: poor appetite, recent weight loss, muscle loss, trouble swallowing. Our developing approach is extracting affirmative or negated mentions of these clinical concepts in an easily extensible and scalable way," said Josiah Meyer.

To accomplish this, Healthleap integrates with a hospital's existing electronic health record system and applies language models to parse free-text clinical notes. Relevant mentions - whether confirmed or explicitly negated - are extracted and fed into the company's risk models alongside structured data. The output is a risk score that surfaces patients who may warrant additional clinical attention. Healthleap is clear that its software does not diagnose patients; it is intended to prompt further review by care teams.

The platform runs its analysis overnight, processing every adult inpatient's full record - including lab results, vital signs, weight measurements, medications, diet orders, diagnoses, and clinician notes. Each morning, updated risk scores are written directly into the care team's existing workflow, accompanied by a dashboard that shows patient trends and supporting clinical detail.

Starting With Malnutrition

Malnutrition proved to be a logical entry point for Healthleap's platform. It is a condition that is widely underdiagnosed in hospital settings, despite its significant impact on patient outcomes. Research estimates that between 20% and 50% of hospital inpatients are malnourished at the time of admission or develop malnutrition during their stay. Multiple studies have associated malnutrition with extended hospital stays, impaired wound healing, higher rates of infection, and elevated morbidity and mortality.

The company has since expanded its screening programs to include delirium, aspiration pneumonia, pressure ulcers, and risk of readmission for congestive heart failure. Meyer noted that the programs targeting aspiration pneumonia, pressure ulcers, and heart failure readmission are still undergoing clinical validation.

Rapid Growth Across Major Health Systems

Healthleap's hospital footprint has grown substantially over the past year, expanding from three hospital partners to more than 50. Its current customer base includes prominent institutions such as Penn Medicine, Cedars-Sinai, Intermountain Health, Houston Methodist, and Emory Healthcare. Meyer said revenue grew more than tenfold over the same period, though he declined to share specific figures.

The company sells three-year contracts structured around a hospital's licensed bed count. It also uses an outcomes-based pricing model, in which the financial return that a hospital's own finance team validates and attributes to the platform forms the basis for contractual guarantees. According to Meyer, every customer to date has seen a hard return on investment of at least five times the contract price, with some reaching more than 20 times the annual total investment.

One notable example comes from the Hospital of the University of Pennsylvania, where Healthleap reports its malnutrition identification program generated $23.8 million in annualized financial impact. Of that total, $6.3 million was attributed to additional reimbursement, while $17.5 million came from reductions in the length of patient hospital stays.

Plans for the Fresh Capital

Healthleap intends to deploy the newly raised funds across engineering, product development, sales, and customer success. The company's longer-term ambition is to build screening programs for more than 40 major health conditions. Beyond expanding its inpatient capabilities, Healthleap also has its sights set on extending the platform into outpatient settings and home-based care, broadening the environments in which its AI-assisted risk identification can be applied.

The funding round reflects continued investor appetite for healthcare AI tools that can demonstrate measurable clinical and financial outcomes, particularly in a hospital environment where identifying complications early can have a direct impact on both patient welfare and institutional costs.