Viz.AI collects $100M to spot more maladies in emergency CT scans

Viz.AI collects $100M to spot more maladies in emergency CT scans

After an FDA clearance earlier this year for its artificial intelligence-powered program designed to spot dangerous aneurysms, Viz.ai has raised $100 million to continue expanding into other conditions.

The venture capital financing also comes after Viz.ai passed the milestone of more than 1,000 hospitals employing its AI platform to read and triage CT scans, the company said—with commercial expansions in Europe, the Middle East and Africa on the tail of Viz.ai’s first five CE marks awarded in 2021.

Meanwhile, Viz.ai launched AI-driven programs for quickly spotting aortic disease and pulmonary embolisms, and it currently has a program for subdural hematoma under FDA review.

The series D round, which bestowed a $1.2 billion valuation on the company, was led by Tiger Global and Insight Partners, with additional backing from Scale Ventures, Kleiner Perkins, Threshold, GV, Sozo Ventures, CRV and Susa.

“We will continue to invest heavily in cutting-edge technology and services to integrate deeply into the clinical workflow, allowing us to automate disease detection, increase diagnostic rates, and enhance workflows across the entire hub and spoke health system,” Viz.ai co-founder and CEO Chris Mansi said in a statement.

In addition, the latest funding will help grow the company’s staff, currently spread among locations in San Francisco, Amsterdam, Portugal and Tel Aviv, Israel. Over the past 12 months, Viz.ai’s headcount has grown from 180 to more than 350, and the company plans to add as many as 200 people in the next year.

The $100 million also tops the company’s most recent funding round, which amounted to $71 million just over one year ago. Viz.ai received its first de novo clearance in 2018, for a program for spotting strokes caused by large vessel occlusions.

This past February, the company presented data at the American Heart Association International Stroke Conference from multiple studies showing its automated programs could speed up procedure times.

One real-world study showed an average reduction of 41 minutes in the time between a stroke patient arriving at a comprehensive stroke center and the first incision in a procedure to retrieve the blood clot. Other analyses examined the AI’s accuracy at determining occlusions of different locations in the brain, as well as its ability to quickly alert care teams of a patient in need.

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