DataRobot recognized in both Completeness of Vision and Ability to Execute

DataRobot, the agentic workforce platform, today announced that the company has been recognized by Gartner^® as a Leader in the Magic Quadrant^™ for Data Science and Machine Learning (DSML) Platforms for the second time.¹ The evaluation was based on specific criteria that analyzed the company’s overall Completeness of Vision and Ability to Execute.

DataRobot helps organizations scale AI faster by making agents practical, cost-effective, and easy to adopt. With ready-to-use agent kits and the flexibility to customize, teams can integrate AI directly into existing systems and workflows with no rip-and-replace required. DataRobot’s platform provides full control over performance, cost, and governance, so leaders can scale AI across departments without adding complexity – delivering AI up to 83% faster and cutting deployment costs by as much as 80%.

To further its commitment to AI innovation, DataRobot recently introduced syftr, a groundbreaking open-source framework aimed at empowering AI practitioners to programmatically discover and deploy optimal agentic workflows tailored for commercial use – prioritizing accuracy, speed, and cost-effectiveness.

“We believe that this recognition validates what our customers experience daily: AI agents that don’t just automate tasks—they make intelligent decisions and drive measurable business outcomes. Our platform is built to help organizations solve high-impact problems with speed, control, and confidence through enterprise-grade governance, full lifecycle management, and seamless orchestration. By consolidating tools and simplifying deployment, we reduce complexity and cost, so teams can focus on what matters most: delivering results,” said Debanjan Saha, Chief Executive Officer at DataRobot.

Over 1,000 organizations worldwide rely on DataRobot to power AI agents that stay aligned with real-world conditions. From optimizing supply chains to automating financial processes, DataRobot believes that it powers agents to continuously retrain and improve as business needs shift—without manual rework. Out of 707 reviews as of June 2 on Gartner Peer Insights^™, DataRobot maintains a 4.6 out of 5 star rating from users, including:

• “DataRobot has effectively transformed the way my team does their work, with the combination of predictive and generative AI and the ease of use, and speed of deployment of AI applications that generates business value. “ – Human Resources, Consumer Goods
• “The best product to continuously generate value with AI in enterprises." – Data Analyst in IT Services
• “It is an incredible product that really reduces development times and delivers better results.” - General Management, Healthcare and Biotech

DataRobot believes that this news is the latest recognition of the company driving agentic AI innovation forward, following the launch of syftr; new AI agent suites for federal, finance, and supply chain organizations; and the acquisition of the open source AI orchestration and computing platform, Covalent. Additionally, DataRobot was named a 2024 Customers’ Choice on Gartner^® Peer Insights^™ Voice of the Customer for Data Science and Machine Learning Platforms.

Learn More

• To view a complimentary copy of the Magic Quadrant report and learn more about DataRobot’s recognition, please visit our website.
• To learn more about DataRobot's capabilities, please register for the webinar “Navigate your AI strategy with DataRobot” on July 10 at 11AM ET.
• To see why users have given DataRobot a 4.6/5 overall rating across 707 Gartner Peer Insights^™ as of June 2, please visit 2024 Customers’ Choice on Gartner Peer Insights^™ Voice of the Customer.²

About DataRobot

DataRobot is agentic AI for the workforce. Our agentic platform enables frontline/business teams to develop, deliver, and govern AI agents and applications that work intelligently and securely with core business processes, infrastructure, and systems — maximizing impact and minimizing risk for organizations across industries. For more information, visit our website and connect with us on LinkedIn.

1. Source: Gartner, Magic Quadrant for Data Science and Machine Learning Platforms, Afraz Jaffri, Maryam Hassanlou, Tong Zhang, Deepak Seth, Yogesh Bhatt, May 28, 2025.

2. Source: Gartner, Voice of the Customer for Data Science and Machine Learning Platforms, Peer Contributors, November 29, 2024.

Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.

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