DataRobot has been named a Leader – again – in the Gartner® Magic Quadrant™ for Data Science and Machine Learning (DSML) Platforms, recognized for its Completeness of Vision and Ability to Execute.
Discover how we believe DataRobot empowers AI teams to go beyond experimentation and deliver real-world impact with production-ready agents. Learn how you can integrate these agents with core systems like SAP and NVIDIA, enforce robust governance, and scale AI across the enterprise—safely and efficiently.
In this session, you’ll get an inside look at DataRobot’s latest agentic AI innovations, hear firsthand from a featured customer about their transformation journey, and watch a live demo of a powerful enterprise agent in action.
Join us to learn:
- How to manage cost, latency, accuracy, and risk—from your first deployment to enterprise-wide scale
- How we think DataRobot simplifies AI operations with built-in guardrails, policy enforcement, and reusable agent templates
- How enterprises are integrating agents into mission-critical workflows using trusted systems and infrastructure
- What’s next on the horizon for agentic AI, including real-time decisioning, autonomous workflows, and cross-system orchestration
Whether you’re just getting started or looking to scale your AI investments, this webinar will give you a practical path forward with agentic AI.
Download the Gartner report
See why DataRobot is recognized as a Leader once again – and how we believe our platform stands out among other evaluated vendors
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.
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.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
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DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively.Tom ThomasVice President of Data & Analytics, FordDirect
The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards. We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence
Rosalia TungarazaPh.D, AVP, Artificial Intelligence, Baptist Health
DataRobot provides us with innovative ways to test new ideas. Given a problem and a dataset, DataRobot allows us to generate multiple prototypes 20% faster. And the process facilitates the learning evolution of our data scientists.
Diego J. BodasDirector of Advanced Analytics, MAPFRE ESPAÑA
The value of having a single platform that pulls all the components together can’t be underestimated. Then there’s the combination of the technology and the collaborative DataRobot team. If either one of those wasn’t there, I would have looked elsewhere.Craig CivilDirector of Data Science & AI
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