Company Overview
About Regard
Regard is a New York-based healthcare AI company — backed with $81.3 million in total funding including a $61 million Series B in July 2024 led by Oak HC/FT with Cedars-Sinai Health Ventures at a $350 million valuation, following a $15.3 million Series A in 2022 and $5 million seed in 2021 — providing health systems with an AI clinical insights platform that analyzes 100% of hospitalized patient medical record data to surface missed diagnoses to care teams, acting as an AI co-pilot for physicians that has surfaced 3 million+ diagnoses and generated $50+ million in incremental revenue for health system partners through improved documentation accuracy. Founded in 2019 by Eli Ben-Joseph, Nate Wilson, and Thomas Moulia (Stanford graduate students) and launched in 2021, Regard serves major health systems including Banner Health (33 acute care hospitals) and Sentara Health (12 hospitals).
Business Model & Competitive Advantage
Regard's AI clinical diagnostics platform addresses the missed diagnosis problem that represents both a patient safety risk and a revenue capture opportunity for hospitals: when a physician admits a patient to the hospital and documents their diagnoses, they are working under time pressure with incomplete review of the patient's longitudinal medical history — secondary diagnoses that are relevant to the current episode of care (comorbidities like malnutrition, acute kidney injury on chronic kidney disease, secondary infections) may be present in prior notes or lab values but not documented by the admitting physician. Missing these diagnoses has two consequences: the patient's care may not be optimized for their full clinical picture, and the hospital's DRG (Diagnosis-Related Group) reimbursement may be lower than warranted because the documentation doesn't reflect the true acuity of the patient's condition. Regard's AI (continuously scanning the full EHR for evidence supporting additional diagnoses and flagging them for physician review) improves both care quality and documentation accuracy.
Competitive Landscape 2025–2026
In 2025, Regard competes in the clinical AI, hospital documentation improvement, and clinical decision support market with Nuance (Microsoft, NASDAQ: MSFT, ambient clinical AI and CDI), Optum (UnitedHealth subsidiary, CDI and clinical analytics), and Artifact Health (clinical documentation improvement, acquired by Cerner/Oracle) for hospital system AI-powered diagnosis capture, clinical documentation integrity, and physician decision support platform adoption. Oak HC/FT's Series B leadership (healthcare-focused VC with portfolio including Flatiron Health and Kyruus) and Cedars-Sinai Health Ventures' strategic participation validate hospital system integration quality. The 2-4x ROI metric (demonstrated at Banner Health and Sentara Health) provides the financial business case for hospital CFO approval. The 2025 strategy focuses on expanding beyond inpatient to ambulatory and specialty care settings, building the AI-powered clinical query workflow for physician response and documentation improvement, and growing the health system enterprise deployment to the 50+ bed hospital segment.
The Regard Story
Founders
Company Timeline
Major milestones in Regard's journey
Leadership Team
Meet the leaders behind Regard
Eli Ben-Joseph
Holds BS in bioengineering and biology from MIT and MS in computer science and management from Stanford. Forbes Technology Council member. Named to Crain's Notable Leaders in Health Care Technology 2025.
Nate Wilson
Stanford graduate who co-founded Regard while on the pre-med track. Contributed to developing the core AI platform and clinical algorithms.
Thomas Moulia
Stanford graduate who co-founded Regard alongside Eli Ben-Joseph and Nate Wilson. Part of the original team that developed the clinical insights platform.
Open Positions
Reddit Discussions
Key Differentiators
Emerging Innovator
Regard is an emerging player bringing innovative solutions to the Healthcare market.
Growth Stage
Regard has achieved $350M in revenue, demonstrating strong product-market fit.
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