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ClosedLoop Employs AI to Target Unnecessary Health Spending

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The Austin, TX-based company has raised $34 million in a series B round to help it accomplish this task.

ClosedLoop.ai is hoping to use artificial intelligence to overcome some of the biggest obstacles in medicine including unnecessary healthcare spending. The Austin, TX-based company has raised $34 million to help it accomplish this task.

The investment round was led by Telstra Ventures with participation from Breyer Capital, Greycroft Ventures, .406 Ventures, and Healthfirst. Angel investors that participated in the round include Adam Boehler (former director of CMMI & CEO of Rubicon Founders) and Sam Palmisano (former CEO of IBM) also participated in the round.

ClosedLoop has developed a data science platform that combines an end-to-end machine learning platform with a comprehensive library of healthcare-specific ML features and model templates. The platform integrates several data science workflows (data onboarding and normalization, automated feature engineering, autoML, and MLOps) and includes capabilities that facilitate experimentation, collaboration, oversight, and management.

ClosedLoop said it would be addressing unnecessary health spending. The firm noted the U.S. wastes 25% of the $4 trillion it spends each year. The company said AI will help providers succeed under Medicare and Medicaid models because it gives them the ability to predict patient-specific outcomes so they can adjust patient care, improve outcomes, and reduce costs. 

“Addressing this is a national imperative; it’s becoming a crisis of access, affordability, and equity" said Adam Boehler, former Director of the Center for Medicare and Medicaid Innovation and CEO of Rubicon Founders, "When the right incentives are paired with AI solutions to predict adverse health events, there is the potential to greatly improve the lives of Americans everywhere.”

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