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Uptake Lays Off 23 People, Says It Scaled 'Too Quickly'


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Brad Keywell, Uptake's founder and CEO, at the tech company's office (Photo via Uptake)

Uptake, the fast-growing Chicago predictive analytics startup led by Groupon co-founder Brad Keywell, laid off 23 employees on Friday.

The tech company said in an emailed statement to Chicago Inno that it eliminated positions across all the company’s departments, but particularly from the product and operations teams.

Uptake said the layoffs were necessary because now that its software is completely built, it doesn’t need as big of a team to maintain it. Uptake, founded in 2014, said that while building the software, it “scaled quickly (maybe too quickly).” Uptake’s predictive analytics platform helps companies keep track of when their machines are likely to break down.

The startup’s tech has been used across several industries, including aviation, rail, mining, and oil and gas. Its customers include Rolls-Royce and Caterpillar. Though Caterpillar, an early investor in Uptake, redeemed its investment stake in the startup in 2017.

Since launching, Uptake has raised about $260 million in venture capital funding. In 2017, the company raised a $117 million Series D round. At the time, the company was valued at $2.3 billion and employed about 800 people. That same year, Uptake also moved into a 134,000-square-foot office at 600 W. Chicago Ave.

It is unclear how many people Uptake employs now, but its staff is significantly smaller than it was at its height, both because of layoffs and attrition. The company laid off 51 people at the beginning of last year and later laid off 150 more.

Though its staff is shrinking, Uptake's business still appears to be expanding. Just last month, Uptake landed its second U.S. military contract with the U.S. Marine Corps to provide its artificial intelligence software to the Marine’s armored recovery vehicles. And last year, Uptake acquired Asset Performance Technologies, an Albuquerque technology company that provides industrial customers like power plants and oil companies with machine failure data.


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