Xerox’s PARC Spins Out Novity, a Breakthrough Predictive Maintenance Venture

NORWALK, Conn. —  Xerox has spun out Novity™, a start-up founded by Xerox’s Palo Alto Research Center that has developed and commercialized industrial predictive maintenance technology.

“PARC’s goal has always been to incubate, launch and commercialize disruptive technologies, and Novity is an excellent example of this model in action,” said Naresh Shanker, chief technology officer at Xerox and President at PARC. “We are proud of Novity’s success to-date and look forward to following the journey as it grows beyond PARC and brings manufacturers closer to the ultimate goal of zero unplanned downtime.”

“Our commitment to existing and future industrial customers is to fundamentally transform the performance of a key part of their operations and ensure that it performs consistently and predictably,” said Markus Larsson, founder and CEO, Novity. “With the combination of our team and PARC’s IP embedded in the Novity TruPrognostics™ engine, we’re well on the way to deliver on our mission to make manufacturers operate cleaner, faster and better.”

The Novity solution was launched by PARC earlier this year and is an Industrial Internet of Things (IIoT) technology that uses equipment sensors and proprietary algorithms to enable industrial manufacturers to see the future health of their production assets without large amounts of historical data. The Novity TruPrognostics engine relies on a combination of machine learning and physics-based models of equipment, predicting failures with 90 percent or better accuracy and lead times of months, not weeks or days.

With the spin out, Xerox will maintain a minority stake in Novity.

About Novity

Founded in 2022, Novity, Inc. is a spin-out from the storied Xerox Palo Alto Research Center (Xerox PARC), drawing on its decades of breakthrough innovation in AI, sensors and the Internet of Things (IOT). The Novity TruPrognostics™ engine provides industrial manufacturers peace of mind and exceptional accuracy in predicting the health of their plant assets and equipment. Learn more at

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