Clinical AI company Aidoc has closed a $150 million Series E round led by Growth Equity at Goldman Sachs Alternatives, assembling a heavyweight investor syndicate that includes General Catalyst, SoftBank Investment Advisors, and NVentures, NVIDIA's venture capital arm, as the Israeli-founded startup bets that its foundation model and enterprise platform can become the operating system for hospital AI. The raise brings Aidoc's total funding to more than $500 million and arrives less than a year after the company secured a similarly sized round, underscoring the velocity of capital flowing into clinical AI at a moment when health systems are under extraordinary pressure to do more with less.
The new capital will fuel development of CARE, Aidoc's Clinical AI Reasoning Engine, a multimodal foundation model trained on tens of millions of medical scans that represents a fundamental departure from the single-task algorithms that defined the first generation of medical imaging AI. Where legacy models were each trained to spot one condition, such as a brain bleed or a pulmonary embolism, CARE can analyze a scan holistically, identify dozens of findings simultaneously, and interpret their clinical context. In FDA evaluations, the model demonstrated sensitivity of 97 percent and specificity of 98 percent, with specificity reaching as high as 99.7 percent for certain conditions, dramatically reducing false positives that plague clinical AI deployments.
"Our mission is to reduce diagnostic errors and improve patient outcomes," said Elad Walach, Chief Executive Officer of Aidoc. "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."
The Foundation Model Advantage
The timing of the raise is no coincidence. In January 2026, the U.S. Food and Drug Administration cleared CARE for diagnostic tasks across 11 disease indicators in a single approval, a landmark decision that brought Aidoc's total FDA clearances to more than 30, the highest number in the clinical AI sector. The clearance validated CARE's architecture: rather than filing separate regulatory submissions for each condition, Aidoc demonstrated that a single foundation model could meet the agency's safety and efficacy standards across a broad clinical spectrum.
That regulatory milestone has given Aidoc a structural advantage. The company says CARE enables development of new clinical indications up to 20 times faster than its previous generation of algorithms. Within three years, Aidoc expects CARE to cover 90 percent of clinically relevant diseases, including cancer and cardiovascular conditions, a scope that would make it one of the most comprehensive clinical AI models ever deployed.
The company is also advancing what it calls "Agentic Radiology," a concept that aims to transform AI from a passive identification tool into an active clinical agent. The system will generate initial draft radiology reports, reducing the time physicians spend on documentation. Instead of searching for abnormalities across thousands of images per case, clinicians are presented with flagged areas for rapid review and confirmation.
"Model accuracy is paramount when touching the core of a physician's work," said Michael Braginsky, Co-founder and Chief Technology Officer of Aidoc. "Foundation models will soon be as ubiquitous in healthcare as ChatGPT is in general use. Scaling clinical AI is an enormous lift -- it requires top-tier talent, powerful infrastructure, deep real-world insight and sustained funding. Success isn't guaranteed, but we believe we're in a unique position to bring this vision to life, and we feel a deep responsibility to do so."
Building the Enterprise Layer
Beyond CARE, the funding will accelerate expansion of aiOS, Aidoc's enterprise-grade platform for deploying and governing clinical AI at scale. The platform functions as a centralized operating layer through which health systems can manage multiple FDA-cleared AI solutions, including both Aidoc's own models and third-party tools. Today, 69 percent of Aidoc's customers run non-Aidoc models on aiOS, a metric that positions the platform less as a product and more as clinical AI infrastructure.
Aidoc's technology now analyzes more than 60 million patient cases annually and is deployed across nearly 2,000 hospitals worldwide. Health systems including Mercy, Hartford HealthCare, and WellSpan Health have made strategic investments in the company. Roxanna Gapstur, President and Chief Executive of WellSpan Health, noted that in one year Aidoc helped WellSpan radiologists analyze more than 200,000 cases, "leading to a significant reduction of critical diagnosis delays."
Through strategic initiatives with NVIDIA and AWS, Aidoc plans to invest over $150 million in the coming years to bring CARE to market, combining high-performance compute and AI development platforms to push the boundaries of model performance and real-time inference at the point of care.
The Road to Public Markets
The investor lineup signals where Aidoc is headed. Goldman Sachs' growth equity division typically backs companies in the late stages before a public offering. CEO Walach has indicated the company is eyeing an IPO within three to five years, a timeline that aligns with the broader maturation of the clinical AI market and the regulatory clarity that recent FDA decisions have provided.
The stakes are significant. According to Johns Hopkins Medicine, 371,000 Americans die annually from diagnostic errors, a crisis compounded by a growing physician shortage and an ever-expanding body of clinical knowledge. Aidoc is betting that clinical AI is no longer optional but essential infrastructure for modern healthcare delivery.
What to Watch
Three developments will determine whether this raise translates into the market-defining position Aidoc is pursuing. First, how quickly CARE expands its disease coverage toward the 90 percent target and whether the FDA continues to grant broad multi-indication clearances. Second, whether aiOS can establish itself as a true industry standard for clinical AI governance, converting its 69 percent third-party adoption rate into a durable platform advantage. And third, whether the IPO timeline holds as the company scales internationally and navigates the regulatory landscape across multiple jurisdictions. With Goldman Sachs now on the cap table and half a billion dollars raised, the expectations are set: Aidoc must prove that clinical AI can operate at enterprise scale without compromising the accuracy that patient lives depend on.
"CARE compresses decades of roadmap into years, bringing forward a future where AI supports every patient encounter."— Elad Walach, CEO, Aidoc