June 10, 2026 — Rad AI announces a strategic partnership with Yale New Haven Health System (YNHH). YNHHS will deploy Rad AI solutions across its imaging network across more than 16 outpatient imaging centers and five hospital campuses to automate and streamline radiology reporting processes.
Across YNHHS’ multi-site network, which manages more than 700,000 radiology exams annually, radiologists often face administrative burdens and significant workflow frictions such as fragmentation, repetitive audio corrections, and manual data entry, which can slow workflows, increase administrative burden, and create additional complexity for radiologists. To accelerate the pace and quality of medical imaging, the facility chose to adopt a radiologist-first AI reporting solution.
Reporting system partnership
In its search for a reporting partner, YNHHS sought a more open and flexible platform that could integrate across its existing clinical and diagnostic systems. Rad AI was chosen for its ability to integrate with existing systems and improve the daily work of radiologists. Rad AI helps reduce the burden of documentation, automate repetitive tasks, and improve workflow efficiency, allowing radiologists to stay focused on patient care rather than administrative tasks.
“As an academic medical center, our priority is always to improve the quality of patient care. As we evaluated the future of our radiology infrastructure, we realized that standard software vendors were unable to keep up with our evolving needs. We needed a true collaborative development partner who could build with us,” said Christopher Whitlow, MD, PhD, YNHHS Radiologist Chair and Chief of the Department of Radiology and Biomedical Imaging at Yale School of Medicine. “Together, we can build specialized solutions while empowering radiologists to fully focus on clinical judgment and provide clearer, actionable insights for patient care.”
Reporting software has long been a staple in radiology, but this collaboration represents a shift from treating reporting as an isolated administrative task to leveraging it as an essential tool for the entire healthcare ecosystem. By combining Rad AI’s ability to seamlessly automate the documentation process with Yale’s clinical research expertise, this partnership will not only improve reporting quality, but also facilitate collaborative clinical research and enable joint development of purpose-built AI tools to meet YNHHS’ unique needs.
“Radiologists have spent years adapting their workflows around systems that were never designed for the realities of modern radiology,” said Doktor Gurson, co-founder and CEO of Rad AI. “As a company founded by radiologists, we understand how important speed, accuracy and clarity are in high-volume environments. This partnership reflects the growing recognition that reporting software must work naturally within the clinical workflow and not create additional friction for the teams delivering care.”
