Kaskada Bags $8M Round to Accelerate ML Workflow

February 10, 2020

Kaskada, a machine learning company that provides a unified platform for feature engineering, has completed a Series A funding round totaling $8 million. The investors include, among others, Voyager Capital, NextGen Venture Partners, Founders' Co-op, and Walnut Street Capital Fund. The total amount raised to date by Kaskada is $9.8 million.

Kaskada helps organizations make better predictions and increase the speed of innovation by integrating data science and data engineering workflows. Kaskada delivers an end-to-end platform for feature engineering and feature serving, including a collaborative interface for data scientists and robust data infrastructure for computing, storing, and serving features in production.

Features are the independent variables that go into machine learning algorithms and are among the most important factors in a machine learning project’s success. Most companies manage feature engineering and feature serving as a non-collaborative, inefficient process. Data scientists design features and data engineers must rewrite the features before they are deployed. This process slows innovation and increases the potential for error. Kaskada provides a unified platform for data scientists and data engineers to share features and eliminate inefficiencies, allowing teams to operate as high-functioning data science factories.

“Deploying machine learning features is a pain for data scientists,” said Davor Bonaci, Kaskada CEO. “Data scientists hand off features to data engineers who must reinvent the wheel to put them into production. Our platform enables feature stores, which let science and engineering teams share features across the organization.”

Kaskada will use the Series A funding to accelerate the company’s growth, expand its team of software engineers, and fulfill more customer demand. The company is delivering its product in the first half of 2020 and is in a growth mode with its team, customers, and partners.

“Kaskada is addressing a huge market need because nearly every company today is pouring significant resources into their data science efforts and very few are seeing results that meet their expectations,” said James Newell, Voyager Capital Managing Director. “The Kaskada team’s prior work at Google Cloud and AWS gave them the chance to see the need for a unified platform for feature engineering as well as the expertise to help companies accelerate and improve the delivery of machine learning capabilities.”

The Kaskada platform for feature engineering and feature serving will be available for beta evaluation by invitation only.

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