Kaskada builds an end-to-end platform for feature engineering and feature serving that unifies data science and data engineering workflows. Its product includes a collaborative interface for data scientists and infrastructure for computing, storing, and serving features in production. The platform aims to eliminate inefficient handoffs between data scientists and data engineers and enable feature stores so teams can share features across an organization. Kaskada said it will deliver its product in the first half of 2020 and is offering beta evaluation by invitation only. The company plans to use the Series A proceeds to accelerate growth, expand its engineering team, and meet customer demand. To date Kaskada has raised a total of $9.8 million. Kaskada is a machine learning studio that computes feature vectors from event-based, streaming data in real time to power recommendations, fraud detection, and other ML features. Its software lets data scientists discover, test, and deploy features from event-based sources in a collaborative, version-controlled environment. The founders say many ML models use stale data and Kaskada's tools aim to improve predictions by fully leveraging up-to-date streaming data. The company, founded in January 2018 and based in Seattle, has raised $1.8 million from investors including Voyager Capital, NextGen Venture Partners, Founders' Co-op, and Bessemer Venture Partners. It employs four people, hired Emily Kruger as vice president of product in March, and expects to grow. Kaskada is backed by VCs and a group of angels that include directors and senior vice presidents from companies such as Google, Twitter, and Yelp.

Total raised

$10M

Funding rounds

2

Latest round

Series A

Latest activity

Feb 2020