The Intelligence Layer for Medical Imaging

Radiologists are drowning in images. The volume of CT scans has exploded, but the number of radiologists hasn't kept pace. Most AI radiology tools address this by flagging a single condition — one tool for stroke, another for pulmonary embolism, another for fractures. a2z Radiology AI takes a fundamentally different approach: one system that triages multiple urgent conditions simultaneously.

Founded in 2024 by Samir Rajpurkar and Pranav Rajpurkar (an Associate Professor at Harvard Medical School), a2z built the first FDA-cleared system to simultaneously triage seven urgent conditions on abdomen-pelvis CT scans. In prospective studies, their AI reduced reporting time by 17.8% and decreased radiologist mental demand by 22.4%.

How It Works

The a2z-Unified-Triage system analyzes CT scans and flags multiple urgent findings in a single pass — no need for radiologists to run seven different AI tools. The platform integrates directly into existing radiology workflows, adding an intelligence layer that helps prioritize the most critical cases without disrupting how radiologists already work.

Why It Matters

The $4.5 million seed round from Khosla Ventures and SeaX Ventures gives a2z the resources to scale across hospital systems. With the global radiologist shortage expected to worsen, tools that make existing radiologists significantly more efficient — without replacing their expertise — represent one of healthcare's most impactful AI applications.