Aidoc Raises $150M as Clinical AI Moves Toward a Hospital OS

Sixty million scans a year and nearly 2,000 hospitals in deployment: that is the operating record Aidoc brought to Goldman Sachs.

On April 29, the Israeli-founded, New York-based clinical AI company announced a $150 million Series E round led by Growth Equity at Goldman Sachs Alternatives, with General Catalyst, SoftBank Investment Advisors and Nvidia's NVentures also participating. The round takes Aidoc's total funding over the past decade beyond $500 million.

But the size of the check is not the most interesting part of the story.

The real asset is the FDA clearance

Earlier this year, Aidoc's CARE foundation model received FDA clearance as what the company described as the first comprehensive foundation model AI for medical imaging triage.

That word “first” matters. Over the past decade, the FDA has cleared hundreds of AI imaging tools, but most have been narrow products: one for lung nodules, another for brain hemorrhage, another for fractures. Each tool came with its own clearance, and a hospital that wanted a full stack had to wire together many vendors.

CARE compresses that bundle of tasks into one model. When a scan arrives, the AI can evaluate more than a dozen urgent findings at the same time. For hospitals, that means fewer fragmented AI purchases and a single model that can cover much of emergency imaging prioritization.

An FDA clearance at that breadth requires clinical evidence far beyond a single-point tool. Aidoc now holds something closer to an operating-system-level permission slip in medical AI.

A data flywheel built from 110 million scans

This is the hard currency behind Aidoc's position:

Medical AI has a familiar split: demos are easy, hospital deployment is hard. Aidoc spent the past few years going deep on emergency imaging triage. When a CT scan comes in, the AI runs first and pushes suspected brain bleeds, pulmonary embolisms, aortic dissections and other life-threatening findings to the top of the radiologist's worklist.

After years of operating inside that workflow, the 110 million-plus cases become training data that later entrants cannot quickly reproduce. CARE's FDA clearance is less about a flashy new architecture than about clinical data collected in the real system.

Where the new money goes

CEO Elad Walach framed the direction clearly:

By 2030, every complex diagnostic decision should be supported by AI that enables earlier detection.

The plan has three parts. First, Aidoc will keep expanding CARE from emergency prioritization into more clinical indications, moving from “which cases are immediately dangerous” toward “which cases show early chronic signals.”

Second, it wants AI to draft imaging reports before radiologists edit them. If that step works, it could remove a large share of routine writing time from the radiology workflow.

Third, Aidoc wants to push aiOS globally by folding these tools into one enterprise platform. Hospitals would no longer manage one-off AI vendors tool by tool, but a unified operating layer for clinical AI.

That last point is especially important. For hospital IT teams, the hardest question is often not which AI is accurate, but how to govern compliance, privacy, versioning and failover when dozens of AI systems are online at once. aiOS is aimed at that governance layer.

What Nvidia's participation signals

NVentures' participation looks different from a purely financial healthcare AI investment.

Nvidia already has Clara, BioNeMo and GPU infrastructure optimized for medical imaging. Backing Aidoc is also a way to bind a high-volume inference customer to its stack. If CARE runs across nearly 2,000 hospitals and supports tens of millions of imaging studies a year, the compute behind that workload becomes a large business in its own right.

Healthcare AI is no longer short of funding. What is scarce is the combination of broad FDA clearance, real clinical deployment and a hyperscale compute partner. Aidoc now has all three, which makes its more than $500 million in total funding easier to understand.

The next question is whether the comprehensive foundation-model approach can move beyond imaging into pathology, ECG or retinal scans. That may be the most important thing to watch in medical AI.

Sources: Aidoc Raises $150 Million Series E Led by Goldman Sachs to Scale Clinical AI for Earlier, Safer Diagnoses (PR Newswire), Exclusive: Clinical AI provider Aidoc raises $150M Series E (Axios), Aidoc raises $150M in funding round (AuntMinnie), CocoLoop, Radiology vendor Aidoc raises $150M from Goldman Sachs and others (Radiology Business)