Glass Health

Glass Health is a clinical decision support platform that uses AI to assist physicians and clinicians in generating differential diagnoses, treatment plans, and clinical assessments — providing a fast-moving AI workspace where clinicians input patient findings (symptoms, vitals, lab results, history) and receive structured clinical reasoning including possible diagnoses ranked by likelihood, recommended workup steps, and evidence-based treatment options. Founded in 2021 in San Francisco and a Y Combinator W23 graduate, Glass Health raised $5 million in seed funding led by Initialized Capital in January 2024, growing to 59,000+ users with notable healthcare founders including Tom Lee (One Medical) and Epocrates team members as backers.\n\nGlass Health's design is built for the clinical workflow — clinicians can quickly enter a patient presentation in natural language and get back a structured differential and workup plan in seconds, useful for initial patient evaluation, complex cases, and educational reference. The platform is designed to augment clinical reasoning rather than replace it, presenting options for clinician evaluation rather than prescribing a single path. The growing user base of 59,000 clinicians represents significant adoption in the physician community, driven by word-of-mouth among medical students and early-career physicians who use it as a reasoning aid.\n\nIn 2025, Glass Health competes in the AI clinical decision support market with UpToDate (Wolters Kluwer, the gold standard clinical reference), DynaMed (EBSCO Health), and emerging AI clinical reasoning platforms for physician decision support tools. The AI-powered CDS market is growing rapidly as large language models prove capable of medical reasoning at near-physician level on benchmarks. The 2025 strategy focuses on expanding to hospital systems (enterprise licensing for inpatient and outpatient clinical teams), building integrations with EHR systems for in-workflow access, and developing evidence validation processes that meet the requirements of clinical institutions adopting AI clinical tools.