DataRobot: A Chief within the 2024 Gartner® Magic Quadrant™ for Information Science and Machine Studying Platforms

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Within the years since Gartner final launched a Magic Quadrant for Information Science and Machine Studying (DSML), the trade has skilled huge shifts. DataRobot has additionally remodeled dramatically from the place we started to the place we stand at this time. The speedy tempo of AI development is unparalleled, and at DataRobot, I’m most pleased with our capacity to harness these improvements to make sure organizations can leverage them safely, with governance, and for impactful outcomes. 

This dedication to driving worth via AI and our steady product enhancement is why we’re thrilled to be acknowledged as a Chief within the 2024 Gartner Magic Quadrant for DSML Platforms. Positioned within the Leaders Quadrant for the primary time marks a major milestone for DataRobot, which we consider displays our transformation and rising affect available in the market. I additionally prolong my congratulations to the opposite corporations acknowledged within the Leaders Quadrant—what a recognition!

As one of many trade leaders on this dynamic panorama, this marks the beginning of a brand new period for DataRobot. Our journey is outlined by ongoing innovation and development, making certain that our present choices are just the start of the groundbreaking developments on the horizon.

Our Journey to the Leaders Quadrant

Gartner evaluates the Magic Quadrant primarily based on a vendor’s capacity to execute and completeness of imaginative and prescient. Corporations use the Magic Quadrant to shortlist know-how distributors, sometimes specializing in distributors within the Leaders quadrant. 

DataRobot is known as a Chief within the Magic Quadrant and we additionally scored the highest for the Governance Use Case within the Crucial Capabilities for Information Science and Machine Studying Platforms, ML Engineering.

Our journey from democratizing AI to a brand new set of customers, to at this time increasing to change into a unified system of intelligence methods, has been transformative. This journey has been propelled by our laser deal with reimagining our person expertise for each generative and predictive AI, including full assist for code-first AI practitioners, broad ecosystem integration, and dependable multi-cloud SaaS and hybrid cloud assist. 

With every launch in Spring ‘23, Summer season ’23, and Fall ‘23, we fortified our product providing. As an end-to-end platform, we offer an in depth vary of capabilities, enabling us to ship enterprise-grade AI-driven options. This evolution displays how our onerous work has stored tempo with the speedy developments within the generative AI house, as we consider is evidenced by our 4.6 out of 5 rating on Gartner Peer Insights primarily based on 538 critiques as of June 26, 2024.

AI-Centric Method

Our platform is constructed on a basis of superior AI applied sciences for practitioners and their associated stakeholders. Our clients leverage refined machine studying algorithms to research intensive datasets, uncovering insights and patterns that drive good and immediate decision-making. DataRobot enhances the platform with ahead deployed buyer engineering groups and utilized AI consultants to speed up worth supply.

Seamless Collaboration

Our aim is to allow synergy amongst members all through the end-to-end DSML lifecycle, addressing the wants of all stakeholders to combine ML and generative AI into enterprise processes. AI practitioners can share use instances, handle recordsdata, and management variations with CodeSpaces, a persistent file system built-in with Git, offering entry to our complete, hosted Pocket book developer setting anytime, anyplace. 

We guarantee speedy deployment of any AI venture – whether or not constructed on or off the DataRobot platform – to any endpoint or consumption expertise, facilitating easy transitions from AI builders to operators. Our unified method to generative and predictive AI  growth, governance, and operations streamlines actions for information science groups, IT personnel, and enterprise customers.

Cross-Surroundings Visibility

The DataRobot AI Platform presents AI observability throughout environments, whether or not cloud or on-premise, for all of your predictive and generative AI use instances. The unified view throughout tasks, groups and infrastructure improve cross-environmental governance and safety for all buyer AI property.  

Enterprise Outcomes

Enterprise Technique Group (ESG) validated DataRobot’s speedy deployment is as much as 83% quicker in comparison with present instruments. Additionally they discovered that it may provide price financial savings of as much as 80%, with a predicted ROI starting from 3.5x to 4.6x, offering the required analytics capabilities for organizations seeking to productionalize 20 fashions. Having served over 1000 clients, together with most of the Fortune 50, DataRobot understands what it takes to construct, govern, and function AI safely and at scale.

Ranked #1 for Governance Use Case

We constructed our governance capabilities to assist our clients set up rigorous insurance policies and procedures that defend their backside line. Our governance framework is designed to uphold the very best requirements of integrity, accountability, and transparency throughout all AI operations. We’re thrilled to have been ranked the very best, with a 4.1 out of 5 governance rating from Gartner for Governance Use Case!

Dedication to Steady Innovation 

Our steady innovation efforts are evident within the over 80 new options now we have launched in generative and predictive AI during the last 12 months. We proceed to innovate and spend money on  the person expertise, providing complete assist for each extremely technical code-first customers, and no-code customers. Keep tuned to our “What’s New” web page to see what now we have in retailer subsequent. We’re already deep into our subsequent groundbreaking launch. 

I’ve been working within the DSML house for over a decade, and I acknowledge that we’re on the cusp of what AI has to supply. What I stay up for most every single day is listening and studying from our clients and companions to securely speed up innovation and worth supply. It’s each a problem and pleasure to work in such a dynamic setting the place nobody is aware of the “proper” reply and we get to check our greatest concepts and see what works. I stay up for an eventful 12 months or two until the following MQ!

And, in the event you’re inquisitive about all developments I talked about, I encourage you all to look at the Information Science and Machine Studying Bake-Off video to see how DataRobot took an issue assertion and a uncooked information set and turned it into an end-user utility and decide for your self.

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Gartner, Magic Quadrant for Information Science and Machine Studying Platforms, Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Raghvender Bhati, Maryam Hassanlou, Tong Zhang, June 17, 2024.

Gartner Crucial CapabilitiesTM for Information Science and Machine Studying Platforms, Machine Studying (ML) Engineering, Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Tong Zhang, Maryam Hassanlou, Raghvender Bhati, Printed June 24, 2024.

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This graphic was revealed by Gartner, Inc. as half of a bigger analysis doc and must be evaluated within the context of the whole doc. The Gartner doc is accessible upon request from DataRobot.

In regards to the writer

Venky Veeraraghavan
Venky Veeraraghavan

Chief Product Officer

Venky Veeraraghavan leads the Product Group at DataRobot, the place he drives the definition and supply of DataRobot’s AI platform. Venky has over twenty-five years of expertise as a product chief, with earlier roles at Microsoft and early-stage startup, Trilogy. Venky has spent over a decade constructing hyperscale BigData and AI platforms for among the largest and most complicated organizations on this planet. He lives, hikes and runs in Seattle, WA along with his household.


Meet Venky Veeraraghavan