Aidoc has secured FDA clearance for an AI-powered computer-aided triage (CADt) solution that detects rib fractures, marking the first FDA-approved clinical AI solution built on a foundation model.

The clearance applies to an updated version of Aidoc’s Rib Fractures triage tool, which is powered by the company’s CARE1 Foundation Model (Clinical AI Reasoning Engine, Version 1). Foundation models, which require extensive data sets and computing resources, are designed to improve AI scalability and accuracy, potentially accelerating development timelines from years to weeks.

Aidoc has been researching foundation models for three years, supported by a partnership with Amazon Web Services (AWS). Under this collaboration, AWS is investing in the expansion of Aidoc’s aiOS platform, which integrates AI tools from multiple vendors. Aidoc is already working on a second-generation foundation model, CARE2, expected to launch in the coming months.

"A year ago, what we're seeing today seemed impossible. Now, it's happening faster than anyone expected," said Michael Braginsky, chief technology officer at Aidoc. "Every major organization will soon have to decide: build a foundation model or leverage one. As this shift accelerates, the real differentiator will be accuracy. Only the most accurate models will drive real impact."

Hospitals have increasingly adopted AI tools, but fragmented solutions can create integration challenges. Aidoc’s aiOS platform is designed to streamline AI deployment by providing a centralized system for integration, monitoring, and governance.

"The future of AI goes beyond simply creating smarter models — it's about seamlessly integrating, scaling and delivering these innovations to end users," Braginsky said. "As AI model development accelerates, managing the resulting complexity becomes critical; without proper controls, rapid growth could overwhelm health systems."

Aidoc’s AI solutions are currently used in over 1,500 medical centers worldwide. The company now has more than 20 FDA-cleared AI tools supporting clinical decision-making across various specialties.

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