DataRobot looks to enterprise AI coders with Zepl acquisition

By acquiring cloud data science and analytics platform vendor Zepl, DataRobot gives data scientists a cloud-native, self-service notebook to write tasks and custom models.

Enterprise AI vendor DataRobot acquired Zepl, a vendor of a cloud data science and analytics platform.

The acquisition gives AI and machine learning coders Zepl's cloud-native, self-service notebook to use their own code in Python, R and Scale while using DataRobot's enterprise features such as collaboration, versioning and security.

DataRobot, based in Boston, did not disclose the amount it paid for Zepl, based in San Jose, Calif. Zepl has raised $13.1 million since it was founded in 2016 by the creators of Apache Zeppelin, a popular open source notebook for data and analytics.

New AI features

DataRobot revealed the acquisition, its eighth since 2017, on May 11, the opening day of its virtual conference, AI Experience Worldwide. The vendor also introduced enhancements to its platform, including Composable ML, Continuous AI, No Code AI App Builder, and Bias and Fairness Production Monitoring.

While enterprises are using more machine learning and AI technology in prepackaged and pretrained forms -- often embedded in standard business applications -- a big market remains for custom-built, company-specific AI applications, said Alan Pelz-Sharpe, principal analyst and founder of Deep Analysis.

With its acquisition of Zepl, DataRobot is trying to meet the challenge of organizing, coordinating, managing and to some degree automating the work of data scientists who build these custom AI applications, Pelz-Sharpe said.

"Through this acquisition, [DataRobot) will give more sophisticated data scientists extensive flexibility to extend their work and use their own code, but the ultimate challenge will be to move the power of AI development to the business analysts and owners," he said.

Through this acquisition, [DataRobot) will give more sophisticated data scientists extensive flexibility to extend their work and use their own code.
Alan Pelz-SharpeFounder, Deep Analysis

Pelz-Sharpe added that in future acquisition deals, it's likely DataRobot will look to focus on the other end of the AI continuum, the business user or "citizen data scientist" who needs more low-code/no-code tools.

Spanning the enterprise lifecycle

Meanwhile, the new Composable ML feature is also aimed at advanced data scientists, enabling them to clone, edit and reconfigure DataRobot's blueprints for the needs of their enterprise's application, the vendor said.

With Continuous AI, which enhances DataRobot's MLOps (machine learning operations) tool, users can set up multiple retraining policies on production models.

Kashyap Kompella, CEO and chief analyst at RPA2AI Research, said DataRobot's product enhancements and the acquisition of Zepl and its data science technology build on the vendor's approach of providing a full enterprise AI platform.

"There are impressive advances in machine learning research, but to put these advances to work in the enterprise is a big challenge," Kompella said. "We need shovels in this AI gold rush, and enterprise platforms like DataRobot that aim to streamline the end-to-end AI lifecycle are tackling this need."

Growth by acquisition

The Zepl purchase is the latest in a string of acquisitions by DataRobot, which raised $270 million in November 2020. The funding surge brought its market valuation to more than $2.7 billion, raising expectation that the vendor will file for an IPO.

The vendor named Dan Wright as its new CEO in March 2021 to replace co-founder Jeremy Achin.

DataRobot's major acquisitions in recent years include collaborative data management platform vendor Cursor in February 2019; machine learning model management vendor ParallelIM in June 2019; and Paxata, vendor of a self-service data preparation platform, in December 2019. Also in June 2020, DataRobot acquired Boston Consulting Group's Source AI technology and entered into a strategic partnership with the firm.

Zepl raised $4 million in its most recent Series A funding round in January 2020, led by SoftBank Ventures Asia and Vertex Ventures, according to Crunchbase.

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