With the unveiling of its new DataRobot AI Cloud, DataRobot made it easier for users to access all its AI and machine learning tools in one place.
DataRobot introduced the AI Cloud platform on Sept. 14. The independent AI and machine learning (ML) vendor said the cloud platform enables organizations to run its software on any combination of public clouds and data centers with the governance and security to protect their businesses.
What DataRobot is doing is unifying the products it has acquired over the past few years, said Mike Gualtieri, vice president and principal analyst at Forrester.
"They have capabilities across the full AI lifecycle that have unified the user experience," he said.
DataRobot has been acquiring different platforms and vendors at a steady pace over the last five years -- eight in all.
Most recently, in July, DataRobot acquired MLOps vendor Algorithmia. In June, it acquired Boston Consulting Group's Source AI technology. And in May, the vendor bought Zepl, a cloud data science and analytics platform vendor.
In 2019, DataRobot acquired Cursor, a data startup vendor; ML model management vendor ParallellM; and Paxata, a self-service data preparation vendor.
By now putting all those vendors' technologies under the cloud, DataRobot is providing users with easy access to its platform, Gualtieri said.
Even so, DataRobot's AI Cloud stands out, said Ritu Jyoti, group vice president at IDC. "They're making multi-cloud a reality," she said.
The cloud's compelling feature is that users now can run DataRobot not only on the DataRobot AI Cloud, but on other clouds such as Google Cloud and AWS or their own data center.
Different users, same cloud
Another selling point of the DataRobot cloud, according to Jyoti, is that it brings data scientists, business analysts and IT specialists under one umbrella. She added that other cloud systems usually focus on one or some of these groups, but not all.
Ritu JyotiGroup vice president at IDC
According to DataRobot, the AI Cloud includes a unified data platform where users can access structured and unstructured data, including visuals, social media, charts and more.
The cloud also features continuous AI bias monitoring for ML operators. This enables operators to trigger the retraining process automatically.
Again, what is most attractive about these features is that they're all being done under the same platform, Jyoti said.
"It is not all organic," she added. "There's a lot of effort that [DataRobot] put in to bring this all together, and it's a combination of organic and inorganic innovation."
She noted that DataRobot is combining not only acquisitions but strategic partnerships, including a recent integration with cloud data vendor Snowflake, to create its multi-cloud platform.
The constellation of AI and ML tools DataRobot has assembled "meets all the critical capabilities that any end user would need," Jyoti said.