DataRobot and Azure make it easy for more users across enterprises to generate business impact with responsible and governable AI at scale.

DataRobot's end-to-end AI/ML Platform unifies all data types, users, models, and environments to deliver critical business insights for your organization. DataRobot can be deployed in two ways on Azure: Customer VPC and Dedicated Managed AI Cloud (DMAIC). The Dedicated Managed AI Cloud deployment option is a dedicated deployment of the latest version of DataRobot delivered as a service, hosted in Azure and managed by DataRobot experts.

DataRobot's end-to-end AI/ML Platform unifies all data types, users, models, and environments to deliver critical business insights for your organization.

AI Leaders, responsible for developing AI strategy in an organization, can use DataRobot's end-to-end platform to address high-value business problems at scale.

AI Builders, responsible for implementing AI strategy, can leverage DataRobot's wide range of tools to develop, iterate, and deploy AI/ML models.DataRobot's end-to-end AI/ML Platform unifies all data types, users, models, and environments to deliver critical business insights for your organization. DataRobot can be deployed in two ways on Google Cloud: Customer VPC and Dedicated Managed AI Cloud (DMAIC). The Dedicated Managed AI Cloud deployment option is a dedicated deployment of the latest version of DataRobot delivered as a service, hosted in Google Cloud and managed by DataRobot experts.

Business Executives, responsible for driving outcomes with AI, can monitor real-time business impact and have peace-of-mind about AI's responsible implementation.

Seamlessly integrated with Azure, the DataRobot AI Cloud platform incorporates the knowledge, experience, and best practices of the world’s leading data scientists to help your business transform into an AI-driven enterprise.

Automated Machine Learning (AutoML) enables all users, regardless of skillset, to quickly build, deploy, and monitor AI models at enterprise scale. AutoML automates AI's most complex, time-consuming, and repetitive tasks.

Machine Learning Operations (MLOps) allows Data Science and IT teams to collaboratively deploy, monitor, and manage ML models in production. From a single pane of glass, users can apply advanced governance, model telemetry, and automated model improvement.

Trusted and Explainable AI ensures that your models are transparent, explainable, and equitable. DataRobot's Explainable AI allows users full model transparency and fix issues before they materialize.

Automated Time Series (AutoTS) automates the development of sophisticated time series models, used to improve forecasts for sales volume, product demand by SKU, staffing, inventory, and many other applications.

No-Code AI App Builder quickly & codelessly turns any model into an AI application. Using DataRobot’s pre-built templates, customized apps can automatically return detailed prediction explanations, perform what-if analysis, and visualize model results, making AI accessible to all.

Data Preparation enables anyone to visually and interactively explore, combine, and shape diverse datasets at enterprise scale.

DataRobot's expert team of data scientists, customer-facing support, and DataRobot University curriculum enables seamless implementation and time-to-value, to help enterprises adopt AI at scale.

Looking for more? For additional options and information, please contact us at azure@datarobot.com.