March 9th, 2021

H2O.ai Placed Furthest in Completeness of Vision in 2021 Gartner Data Science and Machine Learning Magic Quadrant in the Visionaries Quadrant.

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At H2O.ai, our mission is to democratize AI, and we believe driving value from data is a team sport. Data needs to be organized and prepared, often by data engineers, and then models need to be built by data scientists. With models built, they need to be put into production and maintained by IT and DevOps personnel. Finally, these models and workflows need to be accessed by developers to build applications for business users.

Gartner recently published their two Magic Quadrants for Artificial Intelligence, Data Science and Machine Learning (DSML), and Cloud AI Developer Services (CAIDS). The DSML report focuses on AI platforms that support data scientists, and as the title notes, CAIDS is focused on AI services and capabilities for developers.

In the past year, H2O continued to innovate and delivered a comprehensive AI platform, H2O AI Hybrid Cloud. The platform enables organizations to rapidly solve a wide variety of problems using AI, supporting 1000s of use cases.

H2O.ai is a Visionary in Both AI Magic Quadrants

H2O.ai has been positioned furthest for its ability to execute in the Visionaries’ quadrant in 2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms and named a Visionary in the 2021 Gartner Magic Quadrant for Cloud AI Developer Services.

Gartner included H2O.ai in both AI Magic Quadrants, because we are confident, it provides an end-to-end AI Cloud platform that empowers both data scientists and developers.

Gartner 2021 Magic Quadrant for Data Science and Machine Learning Platforms.
Gartner 2021 Magic Quadrant for Cloud AI Developer Services

 

H2O AI Hybrid Cloud and H2O Wave

H2O.ai has continued to rapidly innovate in the past year, delivering H2O AI Hybrid Cloud and H2O Wave. H2O AI Hybrid Cloud is an end-to-end platform that enables organizations to rapidly make world-class AI models and applications for virtually any use case. The platform runs on Kubernetes and works with any infrastructure cloud, data cloud, or on-premises environment.

H2O AI Hybrid Cloud brings automation capabilities across the entire data science lifecycle, including connecting to and preparing data, building and explaining models, and deploying and operating them. Additionally, the platform also makes it easy to build, share & deploy AI applications across an entire organization. H2O AI Hybrid Cloud is optimal for organizations that want to drive value from their data by putting AI into the hands of their business users. H2O AI Hybrid Cloud also ships with an app store to enable developers to publish and share applications with business users.

H2O Wave is an open-source Python development framework that makes it fast and easy for data scientists, machine learning engineers, and software developers to develop interactive AI apps with sophisticated visualizations. H2O Wave integrates with H2O AI Hybrid Cloud and accelerates application development with a wide variety of user-interface components and charts, including dashboard templates, dialogs, themes, widgets, and many more. It can also integrate seamlessly with H2O open source, H2O Driverless AI, and MLOps to easily build and consume models as part of the application.

We believe, our recognition in the Magic Quadrant report reflects a strong vision for making AI accessible for everyone, and this vision is further highlighted by H2O.ai’s contributions to AI for Good and investments in responsible AI capabilities.

H2O.ai Open Source and Community Supports Rapid Innovation

Open source software provides freedom for our customers to innovate. Over 18,000 organizations use our open source machine learning software H2O-3, and H2O Wave, mentioned above, was trending on GitHub when we released it last year. H2O communities have been instrumental in building recipes and applications that the community can reuse. They have also provided us with priceless insights that ensure we’re continuously responding to and delivering on what the market needs. The H2O AI AppStore will further increase collaboration and innovation, enabling data scientists and developers to share and reuse applications that others have built.

One thing that we are really proud of is our community-first approach to business. While we haven’t been able to host in-person meetups due to COVID-19, our community has remained supportive and engaged through various channels including Stack Overflow, Slack, online meetups, and more. Working together we make sure that data scientists and developers of all skill levels can bootstrap their efforts to make the world they want to see. We believe being recognized as a Visionary, is largely due to the strength of our global community.

Sophisticated AutoML including Natural Language, Time-Series, and Image Processing

H2O’s Driverless AI excels in automated feature engineering, model selection, and parameter tuning, helping organizations rapidly build highly accurate and robust models.
Our customers want to be able to combine tabular, language, text, and image data when building certain models, and we’ve invested in delivering AutoML that can rapidly build models that use multiple different types of data.

Responsible AI and Explainability

H2O.ai wants to ensure that AI is used for the betterment of society. We must use AI responsibly, and to do this, we need to understand how AI models work. We’ve built over a dozen different explainability analyses to ensure data scientists can dive deep into their models and ensure they’ve eliminated unintended bias and erroneous results. H2O Wave also helps with explainability, as it enables data scientists to rapidly build user interfaces that simply explain how models work to business leaders.

Another strength of H2O.ai is our focus on explainability. While you have to read the report to find out more, we believe our efforts to make sure AI is accessible and understandable for all continues to be something that helped us in this recognition.

Summary

H2O.ai supports entire organizations from data scientists to business users, we’re leading and accelerating our pace of AI innovation, and our H2O AI Hybrid Cloud works with any infrastructure cloud, data cloud, or on-premises environment. If you’re looking to bring world-class and responsible AI to your department or organization, check-out the H2O AI Hybrid Cloud. Click the Gartner MQ link to download the reports.

 

Gartner, Magic Quadrant for Data Science and Machine Learning Platforms, 01 March 2021, Peter Krensky, Carlie Idoine, Erick Brethenoux, Pieter den Hamer, Farhan Choudhary, Afraz Jaffri, Shubhangi Vashisth
Gartner, Magic Quadrant for Cloud AI Developer Services, 24 February 2021, Van Baker, Bern Elliot, Svetlana Sicular, Anthony Mullen, Erick Brethenoux
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.

About the Author

Read Maloney, SVP of Marketing

Read Maloney is the SVP of Marketing, leading H2O.ai’s efforts to build awareness and grow the business.  Read brings a digital first and customer obsessed approach to marketing.

Read is a combat veteran, serving as a Captain in the United States Marine Corps.  He possesses a background in advanced statistical analysis, due to his time working as a Data Analyst at Honeywell, and 10 years in marketing leadership roles at cloud computing businesses.  He joined AWS in 2010 as a Product Marketer and later built their digital marketing team.  At Oracle, Read led the North American marketing team for their growing cloud business, Oracle Cloud Infrastructure.  Read also led Oracle’s Product Marketing team for Cloud Data Warehousing and Data Science.  He holds a B.S.E. in Mechanical Engineering from Duke University and an M.B.A. from the Foster School of Business (University of Washington).

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