Investment of $150M secured by Aidoc for Artificial Intelligence foundation model
In a significant move for the healthcare industry, artificial intelligence company Aidoc has raised $150 million to develop its Clinical AI Reasoning Engine (CARE), a foundation model designed to assist physicians in clinical decision making.
The funding round, led by General Catalyst and Square Peg, marks a significant step forward for Aidoc's mission to integrate AI into clinical workflows across various specialties, such as radiology, cardiology, oncology, vascular, and neurovascular care.
The CARE model is designed to compress decades of clinical AI development into a few years, aiming to support virtually every patient encounter with AI assistance. The company positions CARE as a scalable, adaptable model that can be rapidly fine-tuned for new clinical indications, making it a foundational AI tool for clinical decision support in healthcare systems.
Aidoc's Chief Technology Officer, Michael Braginsky, expects "foundation models will soon be as ubiquitous in healthcare as ChatGPT is in general use." The company plans to transition all its AI algorithms to run on CARE, accelerating AI integration into clinical workflows.
The funding round also supports the expansion of Aidoc’s enterprise AI platform, aiOS. This platform enables deployment and governance of multiple AI tools with real-time performance monitoring. Aidoc plans to expand aiOS capabilities to transform clinical decision making at scale.
The CARE foundation model is already the basis for two solutions for rib fracture and aortic dissection that have received Food and Drug Administration clearance. Aidoc currently supports more than 150 health systems.
The funding round includes a $40 million revolving credit facility. Strategic initiatives include collaborations with Nvidia and Amazon Web Services. The company's long-term plans focus on broad clinical coverage, deep integration into healthcare workflows, and ongoing expansion of aiOS capabilities.
Since its founding in 2016, Aidoc has been developing broader foundation models, which can be used to detect multiple features in an image. The company started with building point solutions for radiology, such as AI to help detect and triage intracranial hemorrhages and pulmonary embolisms.
With this significant investment, Aidoc plans to invest more than $150 million in the coming years to expand the coverage of diseases to eventually encompass 90% of clinically relevant conditions within three years, including cancer and cardiovascular diseases.
References: 1. Aidoc. (2025, July). Aidoc raises $150 million for Clinical AI Reasoning Engine development. Business Wire. 2. Aidoc. (n.d.). About Aidoc. Retrieved from https://www.aidoc.com/about/ 3. General Catalyst. (2025, July). General Catalyst leads $150 million financing round in Aidoc to accelerate the development of its Clinical AI Reasoning Engine. General Catalyst. 4. VentureBeat. (2025, July). Aidoc raises $150 million to expand Clinical AI Reasoning Engine and aiOS platform. VentureBeat.
- Aidoc, an artificial intelligence company, has raised $150 million to develop its Clinical AI Reasoning Engine (CARE), a model aimed at assisting physicians in clinical decision-making across various specialties.
- The funding round, led by General Catalyst and Square Peg, will help Aidoc transition all its AI algorithms to run on CARE, accelerating AI integration into clinical workflows.
- The CARE model is designed to provide AI assistance for virtually every patient encounter and can be rapidly fine-tuned for new clinical indications.
- The company plans to expand its enterprise AI platform, aiOS, to transform clinical decision-making at scale, enabling deployment and governance of multiple AI tools with real-time performance monitoring.
- The CARE foundation model is already the basis for solutions for rib fracture and aortic dissection that have received Food and Drug Administration clearance, and Aidoc currently supports over 150 health systems.
- Aidoc's long-term plans focus on broad clinical coverage, deep integration into healthcare workflows, and ongoing expansion of aiOS capabilities, with the goal of eventually detecting 90% of clinically relevant conditions within three years, including cancer and cardiovascular diseases.
