Healthleap, a San Francisco clinical AI company whose software reads hospital records to flag inpatients who may have an undiagnosed condition, announced $38 million in combined seed and Series A funding on October 7, 2026. The investors are Sequoia Capital, First Round Capital and Hummingbird Ventures, according to the company's announcement.
The company started with malnutrition and plans to use the money to apply the same approach to other conditions. Its footprint figures vary by source. The announcement on Healthleap's website says it screens every adult inpatient, every day, at more than 20 hospitals. Chief executive Josiah Meyer told TechCrunch the platform is deployed in more than 50.
The round
TechCrunch reported the structure: an $8 million seed round co-led by Sequoia and First Round, and a $30 million Series A led by Hummingbird. The company is not disclosing its valuation.
Siblings Josiah and Jemima Meyer founded Healthleap in South Africa in 2022. Jemima is a clinician, and the company first offered a clinical nutrition tool she had built for dietitians, TechCrunch reported. Meyer told the outlet that Healthleap grew from three hospital partners to more than 50 over the past year and that revenue grew more than tenfold, without giving figures.
The announcement names Penn Medicine, Houston Methodist, Cedars-Sinai and Emory Healthcare among the health systems using the software. TechCrunch also lists Intermountain. Healthleap says the funding will go toward screening for more conditions and hiring across engineering, sales, customer success and product.
What the software does
Healthleap connects to a hospital's electronic health record. Meyer told TechCrunch that each night it analyzes every adult inpatient's record, including labs, vital signs, weights, medications, diet orders, diagnoses and clinicians' notes, and each morning writes a risk score into the care team's existing workflow. Language models pull signals from free-text notes, such as references to recent weight loss or difficulty swallowing.
The company says the software does not diagnose. It flags patients for further review, and clinicians decide what happens next. Because it reassesses patients daily as new information reaches the record, it can catch risk that develops after admission, MobiHealthNews reported. The announcement contrasts this with the common practice of two screening questions asked once, at admission, which patients who are sedated, confused or very ill may not be able to answer.
Healthleap says up to half of hospitalized patients are at risk of malnutrition, while fewer than 9% are formally diagnosed. That gap is the market it is selling into.
The evidence behind the claims
Healthleap cites a peer-reviewed study of its malnutrition model, published in Applied Clinical Informatics in 2025. It was a retrospective validation using electronic records from 106,449 patients over 3.75 years. The paper's competing-interest statement says four of its nine authors are Healthleap employees and three are advisers to the company.
The authors report an area under the receiver operating characteristic curve (AUROC) of 0.92 on the first day of hospitalization, measured against malnutrition coded at discharge. Using each patient's highest risk score across the stay, the figure rose to 0.95. They report similar results against dietitian-recorded malnutrition, and say the model outperformed the nurse-administered, modified Malnutrition Screening Tool the hospital used in practice.
The study measured how closely the model's risk scores tracked diagnoses recorded in the chart. It covered malnutrition only, and it did not set out to test whether using the software changes patient outcomes.
The operational and financial figures attached to the round come from the company and its investors. Healthleap says its malnutrition program at the Hospital of the University of Pennsylvania produced $23.8 million in annualized financial impact: $6.3 million from additional reimbursement and $17.5 million from shorter stays, according to TechCrunch. Alfred Lin, a partner at Sequoia, said in the announcement that one hospital saw "39% more malnutrition cases identified and treated." TechShorts found no independent evaluation of either figure.
What hospitals should know
The product touches more than one hospital function. Clinical teams act on the flags, but the reimbursement part of the financial case lands with clinical documentation and revenue cycle teams, because it depends on more malnutrition diagnoses being documented and coded. Meyer told TechCrunch the company sells three-year contracts priced by licensed bed count, alongside an outcome-based pricing model tied to return on investment that the hospital's finance team validates.
Under Medicare's MS-DRG system, a secondary diagnosis classed as a major complication or comorbidity (MCC) can move a stay into a higher-paying group, and some payers scrutinize malnutrition claims specifically. Centene's severe malnutrition payment policy, CC.PP.145, says its plans will deny the payment difference between a DRG billed with severe malnutrition as a secondary MCC and the DRG without it, unless the inpatient record meets the policy's documentation criteria. The policy says plans use paid claims data and a proprietary algorithm to pick claims for retrospective audit.
None of this suggests the reimbursement Healthleap reports is improper. It does mean the reimbursement figure in any vendor case study depends on documentation practice and payer mix at the hospital that produced it. A result from one academic medical center will not carry over unchanged to another.
What happens next
TechCrunch reported that the platform screens for delirium as well as malnutrition, and that programs for aspiration pneumonia, pressure ulcers and congestive heart failure readmission risk are still undergoing clinical validation. The announcement adds hospital-acquired infections to the expansion list. Meyer told Fierce Healthcare the company aims to reach "more than 40 conditions" and to bring the platform to "hundreds of hospitals in the coming year."
The published validation covers malnutrition alone. The markers to watch are published validation results for the newer programs, named health systems deploying them, and whether any hospital or researcher outside the company reproduces the reported outcome figures.
Sources
- Healthleap. "Healthleap Raises $38M to Help Hospitals Find Patients with Undiagnosed Conditions." October 7, 2026. https://healthleap.ai/series-a
- TechCrunch (Ram Iyer). "Healthleap raises $38M for its AI that flags hospital patients who may need a closer look." October 7, 2026. https://techcrunch.com/2026/10/07/healthleap-raises-38m-for-its-ai-that-flags-hospital-patients-who-may-need-a-closer-look/
- MobiHealthNews (Eve Bender). "Healthleap raises $38M for AI patient screening." October 8, 2026. https://www.mobihealthnews.com/news/healthleap-raises-38m-ai-patient-screening
- Fierce Healthcare (Cailey Gleeson). "Healthleap banks $38M for AI screening platform that catches undiagnosed conditions." October 8, 2026. https://www.fiercehealthcare.com/finance/healthleap-banks-38m-funding-backed-sequoia-capital-first-round-capital-and-hummingbird
- Bernstein AM, et al. "Artificial Intelligence-Based Hospital Malnutrition Screening: Validation of a Novel Machine Learning Model." Applied Clinical Informatics, 2025;16(5):1646-1657. https://pubmed.ncbi.nlm.nih.gov/40523638/ (full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12618146/)
- Centene Corporation, via Sunshine Health. "Payment Policy: Severe Malnutrition, CC.PP.145." Accessed October 17, 2026. https://sunshinehealth.com/content/dam/centene/Sunshine/medicare/allwell/CC.PP.145.pdf