Israeli Startup UltraSight Secures $24 Million to Expand AI Ultrasound Tech

Israeli startup UltraSight has raised $24 million in a Series B round to expand its AI-driven ultrasound guidance technology, Navigator, helping hospitals tackle acute labor shortages.

GeektimeAuthor: Oshri Alkesty
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Israeli Startup UltraSight Secures $24 Million to Expand AI Ultrasound Tech
Photo: Geektime / מקור: אולטרה-סייט

The Israeli startup UltraSight has developed an artificial intelligence-powered technology designed to simplify ultrasound diagnostics, addressing a severe workforce shortage in American hospitals. Founded in 2018 by Itai Shoshan (CTO), Yaron Lipman (scientific advisor), and Achi Ludomirski (Chief Medical Officer), the company is led by CEO Davidi Vortman. UltraSight announced the completion of a $24 million Series B funding round.

The investment round was led by the Alive HealthTech Growth Fund, with participation from Deep Insight, Star51 Capital, Connecticut Innovations, eHealth Ventures, and previous backers including Mayo Clinic Ventures, NYU, and Iron Nation. With 24 employees—19 in Israel and the rest in the US—UltraSight aims to expand its hospital footprint significantly.

AI-Powered Ultrasound Guidance

UltraSight's flagship product, Navigator, uses deep learning models on 2D echocardiography (B-mode) to guide non-specialized medical staff in performing accurate heart ultrasounds. The interface provides real-time instructions on how to hold and maneuver the ultrasound probe to achieve diagnostic-quality images without requiring extensive technician training.

"In 2021, the product knew how to guide a person to a quality echo image... Since then, two substantial things have happened: Navigator is in real use in the field, not a demonstration, and based on this capability we built additional layers," said CEO Davidi Vortman.

Overcoming Healthcare Challenges

The technology is positioned to combat rising labor shortages and increasing demand for echocardiograms in US healthcare facilities. By leveraging portable ultrasound devices and automated quality assessment, the system selects the best clip for standard views, streamlining end-to-end clinical workflows.

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