Machine learning is all the rage in big tech, but still largely unavailable to most companies that don’t have the resources or the knowhow to build it. Seattle startup Kaskada wants to change that.
The company just raised a $8 million Series A round to grow its software platform for big companies to deploy machine learning — systems that can learn from experience without requiring additional programming. The round brings the startup to $9.8 million in lifetime funding, and investors include Voyager Capital, NextGen Venture Partners, Founders’ Co-op, and Walnut Street Capital Fund.
Kaskada’s software is geared primarily toward enterprise companies outside the tech world that still rely on some form of data science for their products. The startup wants to make it easier for the two main roles involved with machine learning products — data scientists and data engineers — to work together.
Data scientists design new features, and then engineers often have to rewrite them because available tools for each side make the other’s job harder, Kaskada executives said. This can slow innovation and introduce errors.
“In the market today, there are great tools for data science and great tools for data engineering,” Kaskada CEO Davor Bonaci said in an interview with GeekWire. “But the thing is, these two people need to collaborate together, and there is no software that enables them to work together efficiently.”
The company has between 10 and 20 employees, and the cash infusion will help it expand the software team. A beta version of Kaskada’s platform is available via invitation only, and the company plans to launch its first product in the first half of the year.
Machine learning has become such a big trend, Bonaci says, because it is the driving force behind the ability to personalize apps and services. And that is very in demand right now.
Bonaci spent four years as a senior software engineer at Google and another five at Microsoft. CTO and co-founder Ben Chambers also came from Google. Emily Kruger, an ex-Amazon Web Services senior product manager, joined a few months after the co-founders established the company as vice president of product.
While at Google, Bonaci and Chambers discovered that machine learning tools they worked on didn’t make sense for most users beyond other big tech companies. They required huge budgets and lots of people to operate.
“Existing software and open-source projects in the market are mostly built by and for such big tech companies,” Bonaci said.