Healthleap Secures $38M to Expand AI Screening for Undiagnosed Hospital Conditions

Healthleap, an AI startup, has secured $38 million to expand its platform that scans patient records for undiagnosed hospital conditions. The investment will fuel the scaling of its AI workflow, which has demonstrated significant financial and clinical impact in over 50 hospitals, to cover more than 40 health conditions.

Mateo Rossi

October 9, 2026 · 5 min read

Healthleap, a startup using artificial intelligence to scan patient records for signs of undiagnosed illnesses, has secured $38 million in a combined seed and Series A funding round. The investment, led by prominent venture capital firms, validates the company's approach to tackling a persistent problem in healthcare: conditions that are often overlooked during a hospital stay, leading to poorer patient outcomes and significant financial losses for health systems. The new capital is earmarked to scale Healthleap's platform, which is already deployed in over 50 hospitals and has demonstrated substantial financial and clinical impact at major U.S. medical centers.

Founded in 2022 by siblings Jemima and Josiah Meyer, Healthleap aims to move hospitals beyond static, manual screening methods that frequently fail to identify at-risk patients. The company plans to use the funds to expand its platform's capabilities from an initial focus on malnutrition to cover more than 40 major health conditions, while also growing its engineering, product, and sales teams to support a broader rollout into hundreds of hospitals.

Strategic Investment Fuels AI Platform Expansion

The $38 million financing consists of an $8 million seed round co-led by Sequoia Capital and First Round Capital, followed by a $30 million Series A round led by Hummingbird Ventures. While Healthleap has not disclosed its valuation, the backing from these high-profile investors signals strong confidence in its technology and business model.

The company's origin stems from a direct clinical need. According to a report from TechRepublic, co-founder Jemima Meyer, a clinical dietitian, recognized that many hospital patients were receiving crucial nutritional interventions far too late. This insight formed the basis for a platform designed to provide an earlier, more accurate signal of patient risk.

Investors have been drawn to the platform's demonstrated ability to deliver tangible results. "We were immediately drawn to Healthleap’s bold vision: imagine if every hospital could use real-time AI to spot overlooked clinical risk, improve patient care, and unlock meaningful reimbursement revenue,” said Josh Kopelman, a co-founder and partner at First Round Capital, in a statement. “That’s exactly what Healthleap is delivering and more, starting with disease-related malnutrition and rapidly expanding across conditions to save lives and hospitals money.”

Healthleap's AI Workflow: From Data to Clinical Action

Healthleap's platform is engineered to replace outdated screening protocols, such as simple admission surveys that can easily miss sedated, confused, or critically ill patients. By integrating directly with a hospital's electronic health record (EHR) system, the AI provides a continuous and comprehensive assessment of every adult inpatient, every day.

The process unfolds in a series of automated steps designed to translate vast amounts of patient data into a clear, actionable signal for care teams:

Comprehensive Data Ingestion: Each morning, the platform ingests the complete medical record for every patient. This includes structured data like laboratory results, vital signs, and medication orders, as well as unstructured information from clinicians' notes. This dynamic approach contrasts sharply with static screening methods that capture only a single moment in time.
AI-Powered Analysis: Healthleap deploys language models to parse the unstructured text in physician and nursing notes, extracting clinical indicators such as recent weight loss, deteriorating appetite, or muscle atrophy. This information is synthesized with structured data to generate a daily risk assessment for specific conditions that are often underdiagnosed.
Seamless Workflow Integration: Crucially, the platform's output is delivered directly into the care team's existing EHR workflow. "Each morning, we write a risk score into the care team’s existing workflow," co-founder Josiah Meyer explained to TechCrunch. This avoids the need for clinicians to learn a new system or log into a separate dashboard, a common barrier to technology adoption in hospitals. The system functions as an early warning, feeding a cleaner signal to downstream clinical documentation and coding teams.