TLDR: Aidoc, a leading medical AI company, has successfully secured $150 million in new funding, co-led by General Catalyst and Square Peg, with participation from NVentures (NVIDIA’s venture arm) and major U.S. health systems. This investment, which includes a $40 million revolving credit facility, brings Aidoc’s total funding to $370 million. The capital will primarily fuel the accelerated development of CARE™, the company’s clinical-grade foundation model, and expand its AI solutions into new areas like oncology and cardiovascular disease, aiming to support 100 million patients annually within three years.
Aidoc, a pioneering force in medical artificial intelligence, announced on July 23, 2025, the successful closure of a $150 million financing round. This significant investment is set to propel the expansion of its clinical AI diagnosis solutions and further develop its foundational AI models. The funding round was co-led by prominent venture capital firms General Catalyst and Square Peg, with notable participation from NVentures, NVIDIA’s venture capital arm, marking its first investment in Aidoc. Additionally, four major U.S. health systems—Sutter Health, Hartford HealthCare, Mercy, and WellSpan Health—joined as strategic investors, underscoring the industry’s confidence in Aidoc’s vision. This latest round also incorporates a $40 million revolving credit facility, elevating Aidoc’s total funding to an impressive $370 million since its inception in 2016.
The primary objective of this substantial capital infusion is to accelerate the development and deployment of CARE™ (Clinical AI Reasoning Engine), Aidoc’s cutting-edge clinical-grade foundation model. CARE™ is designed to assist physicians in clinical decisions and has already powered two FDA-cleared solutions, adding to dozens of prior approvals. Michael Braginsky, Aidoc’s CTO, highlighted the transformative speed of their new technology, stating, “What used to take decades now takes far less time, we can build each algorithm ten times faster. We used to develop one or two algorithms a year; this year alone, we’ve created fifteen, providing doctors with more comprehensive insights into patient conditions.” He also noted NVIDIA’s strong interest, adding, “NVIDIA saw the results of our research, which lasted more than two years. They’re all in, because this is a huge boost for AI.”
The funding will also support the expansion of aiOS™, Aidoc’s enterprise-grade platform for deploying and governing clinical AI at scale. The company plans to invest over $150 million in strategic initiatives with NVIDIA and AWS to bring CARE™ to market, combining high-performance computing and AI development platforms to redefine model performance and efficiency. This investment will also facilitate the seamless integration of both Aidoc and third-party AI solutions, fostering an open ecosystem.
Aidoc’s AI-powered tools currently support care for over 45 million patients annually across more than 150 health systems globally, including leading partners like Mount Sinai Health System, Yale New Haven Health System, University of Miami, Temple Health, and Northwell Health. The company aims to significantly expand its reach, targeting 100 million patients within the next three years. Aidoc’s solutions are already installed in thousands of hospitals worldwide, offering FDA-cleared products that provide real-time alerts for life-threatening conditions such as brain hemorrhages, aneurysms, fractures, aortic aneurysms, pulmonary embolisms, and strokes.
Also Read:
- Vanta Secures $150 Million in Series D Funding, Reaching $4.15 Billion Valuation
- Everlab Secures US$10 Million Seed Funding to Scale AI-Powered Preventive Healthcare Globally
Elad Walach, CEO of Aidoc, articulated the company’s core mission: “Our mission is to reduce diagnostic errors and improve patient outcomes. CARE compresses decades of roadmap into years, bringing forward a future where AI supports every patient encounter, helping physicians provide the care they believe their patients deserve.” This investment comes at a critical time when healthcare faces challenges like diagnostic errors, physician shortages, and an ever-expanding body of clinical knowledge, all of which clinical AI aims to address by improving decision-making, flagging high-risk findings, and automating follow-ups.
