Crain’s: Image-recognition startup becomes 50th to graduate from NYU Poly

  • Client News
  • Client: NYU Polytechnic School of Engineering

Via Matthew Flamm’s article in Crain’s New York Business:

Clarifai, a startup that just a year ago consisted of one person in NYU Poly’s Varick Street incubator and now comprises 11 people in the Flatiron district, has raised $10 million in a Series A round led by Union Square Ventures.

The 18-month-old company, which develops image-recognition software, announced the funding round on Tuesday. It moved out of its incubator space last week to the Flatiron district, becoming the 50th startup to graduate from NYU Polytechnic School of Engineering’s three incubators, which launched with the Varick Street location in July 2009.

Combined, those 50 companies are valued at $721 million, according to tallies by Kurt Becker, who oversees the incubators in the new role of vice dean for research, innovation and entrepreneurship. Their previous longtime director, Micah Kotch, departed in September.

The incubators—which have backing from the city’s Economic Development Corp.—have long been considered a stellar example of how public, private and educational partnerships could foster new businesses, but Mr. Becker, a physicist and entrepreneur, says they can do more. He is increasing collaboration with the private sector and developing a closer relationship between the entrepreneurs inside the incubators and the faculty and students in the surrounding academic community.

Together with individual managers at the three sites, Mr. Becker also plans to help startups make the leap to the real world. “For our next five-year strategy, we will put more focus on getting companies ready to exit,” he said.

In the meantime, Clarifai, which already has a wide range of paying customers for its image-recognition technology, is planning to invest the $10 million in new staff. Founder and CEO Matthew Zeiler expects to more than double head count over the coming months to 25.

“We want to ramp up the team and hire all the best machine-learning researchers,” he said. “Right now it’s all engineering and research employees. We also want to grow the business and sales side.”

For the original article, please click here.

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