| January 4, 2016

Keep Watch in 2016 on These Seattle Startup Stars, Including Carlos Guestrin’s (Stanford CS ’02) Dato

Amazon.com, Expedia and other local technology giants are growing with such increasing speed in the past several months that it’s sometimes easy to forget that the Puget Sound region’s scene of smaller companies is booming as well.

Companies in the area raised $1.95 billion in investments during 2015, according to data from Pitchbook Data. A study last year found there are 700 startups just within Seattle.

Many fall into the software category — a well-established area here — though gadgets and biotechs are picking up steam, too.

Amazon.com, Expedia and other local technology giants are growing with such increasing speed in the past several months that it’s sometimes easy to forget that the Puget Sound region’s scene of smaller companies is booming as well.

Companies in the area raised $1.95 billion in investments during 2015, according to data from Pitchbook Data. A study last year found there are 700 startups just within Seattle.

Many fall into the software category — a well-established area here — though gadgets and biotechs are picking up steam, too.

We reviewed 2015’s big tech announcements, funding rounds and new companies emerging to pick out some of the most promising stars among startup companies.

Here it is, our unscientific list of companies that achieved something great in 2015 and should be watched in 2016.

Dato

Location: Seattle, Fremont

Funding raised: $26.75 million

Number of employees: 45

Machine-learning startup Dato, which changed its name from GraphLab in January, inked a funding round worth $18.5 million in 2015, led by Paul Allen’s Vulcan Capital

The startup is headed by University of Washington professor Carlos Guestrin, who was recruited to the region by Jeff Bezos. Dato helps big companies such as Pandora and Zillow make sense of the massive amount of user data they collect.

Next: More than 50,000 developers use the Dato platform, and the company is working on features to make machine learning easy for companies to implement.

READ THE FULL STORY

Posted by Siebel Editor

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