DataRobot and Microsoft has announced a partnership to accelerate AI adoption in the enterprise. The collaboration will include integrations with Microsoft Azure OpenAI Service, Azure Machine Learning, and Azure Kubernetes Service (AKS), making it possible for data scientists to use large language models (LLMs) to assist with writing code. This will enable DataRobot and Microsoft customers to more easily build, deploy, and manage end-to-end enterprise-ready AI solutions on Microsoft Azure.
“The integration of DataRobot with Microsoft’s generative AI and ML services delivers customers breakthrough innovation and experiences for machine learning experimentation and production work built on Azure’s differentiated and scalable platform,” said Venky Veeraraghavan, Chief Product Officer at DataRobot. “Generative AI will drastically modernize the development, interpretation, and adoption of AI use cases, and we’re thrilled to be incorporating Azure OpenAI Service deeply into our product experience for our customers to derive even greater value from their AI investments.”
Azure OpenAI Service’s models can now be used directly inside DataRobot, making it easier to build models using code and no-code methods, and deploy and govern them with Azure Machine Learning. This new, seamless experience is one of the first steps in how DataRobot uses LLMs to help accelerate adoption of generative AI for businesses of all sizes.
“The need for seamless, strategic partnerships when it comes to delivering critical customer needs and generating tangible business outcomes has perhaps never been more important than it is today in the current AI landscape,” said Eric Boyd, Corporate Vice President, AI Platform at Microsoft. “We’re thrilled to announce our partnership with DataRobot, a company built for breaking down complex AI problems, and further cement our commitment to meet customers where they are as we help businesses accelerate their AI journey and achieve bottom-line goals.”
New integrations will improve the efficiency of ML practitioners and builders, enabling organizations to derive value from AI:
- Integration with Azure OpenAI Services: DataRobot Notebooks Code-Assist is now available in Preview for all customers who can use conversational prompts to generate data preparation and modeling code in Python that uses the full context of the business use case and available data.
- Integration with Azure Machine Learning: This allows users to easily deploy trained models, using scoring code, from their DataRobot registry to Azure Machine Learning managed endpoints, and monitor these deployments in DataRobot. This integration also enables automated model compliance documentation for both DataRobot and Azure Machine Learning models.
- Future-Ready AI-optimized Infrastructure: With full support for Microsoft Azure Kubernetes Service, the DataRobot AI Platform also now includes a variety of deployments such as self-managed deployments on Azure Kubernetes Service and managed single-tenant SaaS.
“Interoperability across the ecosystem coupled with generative AI is paramount to successful AI and ML deployments. Integrations like the one we see here between Microsoft and DataRobot will transform the way companies innovate, operate and work,” said Andy Thurai, VP & Principal Analyst of Constellation Research. “In recent market research, we see businesses that widely adopt AI are expected to increase their local economies’ GDP by 26% by 2030 in both revenue and savings from productivity gains. This is all thanks to the transformative power of AI.”
“A complete AI lifecycle platform is invaluable in optimizing the effectiveness and efficiency of our growing data science team,” said Craig Civil, Director of Data Science and Artificial Intelligence at BSI. “The DataRobot AI Platform provides full flexibility to integrate within our current ecosystem, including pulling data directly from Microsoft Azure to save time and reduce risk, and providing insights through Microsoft Power BI. This flexibility drew us to DataRobot, and we look forward to leveraging the integration with Azure OpenAI to continue to drive innovation.”