Kaskada, a Seattle-based machine learning startup that helps data scientists and data engineers collaborate, announced it closed on an $8 million Series A round Tuesday.
Usually, when companies develop features — independent variables that are essential to machine learning algorithms — data scientists design them and data engineers have to rewrite them before they get deployed. This method, says Kaskada CEO and co-founder Davor Bonaci, slows down innovation, increases the potential for error and, overall, “creates an organizational friction” within a company.
With a collaborative interface and data infrastructure, Kaskada’s end-to-end platform sits in the middle of these two parties, allowing them to work both faster and smarter.
“With our software, which sits between data science and data engineering, you can do things once,” Bonaci told Built In. “You can enable both sides of your team to focus on things they do well without blocking each other.”
The company’s leadership team is full of tech veterans. Bonaci and his co-founder Ben Chambers worked at Google and Emily Kruger, a former senior product manager at Amazon Web Services, is the company’s vice president of product. Generally speaking, Bonaci says, big tech companies like these tend to dominate the machine learning sector at the expense of other industries. Kaskada can be a way for these sectors to catch up and build superior products more efficiently.
“What we’ve been particularly successful at, I think, is being able to look at things with fresh eyes and kind of ignore some things that, perhaps, big companies have,” Bonaci said. “I think that enabled us to be successful thus far.”
This most recent funding round brought Kaskada’s total money raised to $9.8 million and the platform is scheduled to launch in the next few months. Bonaci says the company plans to use the $8 million to improve the platform and potentially add about 10 more employees to its roster.
Going forward, Bonaci sees a bright future for both Kaskada and machine learning more broadly.
“When you look at software up to now, or until recently, everybody had a kind of equal experience,” Bonaci said. “But machine learning is changing things. It’s making it possible to personalize software so that your experience is tailored to your interests, your desires and helping you get your job done. This has only addressed a few early scenarios, like recommendation engines and so on, but I see a huge potential in the ability to personalize experiences across any product."