a2z Radiology AI

a2z Radiology AI is a healthcare AI company founded in 2024 and based in Boston, Massachusetts, co-founded by Harvard Medical School AI researcher Pranav Rajpurkar together with technology executive Samir Rajpurkar. The company was created to close the gap between the volume of abdomen-pelvis CT scans radiology departments must read and the limited time available to flag urgent findings quickly.

Its flagship product, a2z-Unified-Triage, is an FDA-cleared system that analyzes abdomen-pelvis CT studies for seven urgent conditions in a single pass and reorders the radiologist worklist so flagged cases surface first. An image-to-report drafting capability is in research to further shorten reporting time. Customers are hospital radiology departments and health systems handling high CT volumes, deployed alongside existing imaging infrastructure rather than replacing it.

1. Multi-condition triage: Flags seven urgent abdomen-pelvis CT findings in one automated pass instead of separate single-condition tools.

2. Worklist reprioritization: Moves flagged urgent studies to the top of the radiologist worklist automatically.

3. FDA clearance: a2z-Unified-Triage holds FDA clearance for the U.S. market, covering simultaneous multi-condition triage.

4. Reporting time reduction: Independent testing showed AI assistance cut reporting time and increased radiologist confidence.

5. Report drafting (research): Image-to-report drafting capability is being developed to further speed up interpretation.

6. Existing infrastructure fit: Deploys within a hospital's current imaging and PACS workflow without new scanners.