Scale and Maintain the Integrity of all your Predictive AI Models

New predictive AI functionality to help you scale predictive AI solutions and ensure model integrity and performance from build through deployment for DataRobot built models or custom models.

Confidently Deploy and Govern GenAI Solutions

Datarobot delivers testing, optimization and AI observability to enable customers to create production-grade AI applications, observe and intervene in real-time and govern and optimize the infrastructure.

Closing the Generative AI Confidence Gap

DataRobot’s newest release gives you the confidence to achieve real-world value with generative AI, enabling you to rapidly build with optionality, govern with full transparency, and operate with correctness and control.

Powering Generative AI from Vision to Value – Summer ‘23 Launch

DataRobot gives you the only open solution that delivers on your generative and predictive AI needs from experimentation through production and consumption across any cloud.

The DataRobot AI Platform is the only open, complete AI lifecycle platform leveraging machine learning that has broad interoperability, end-to-end capabilities for Experimentation and Production and can be deployed on-premises or in any cloud infrastructure. Exciting new features, a redesigned Experimentation user interface, new integrations with Snowflake and many more advancements make this a very exciting release for DataRobot customers.

Realize value at production scale and maximize your existing investments with the February DataRobot AI Platform release, including new features that provide speed, insights, and ecosystem advancements. This includes native integrations with Snowflake, the introduction of Python Scoring Code, and support for data scientists and software developers to create a seamless user experience

Realize business value from AI more quickly with the January DataRobot release and new features that provide speed, flexibility, and ecosystem advancements. New, hosted Notebooks allow the development of AI/ML projects with code-first or code-free experiences. See 21% faster results* when choosing Quickrun Autopilot mode with DataRobot AutoML. Save time by building No-Code AI Apps directly from a model leaderboard. 

The new, user-friendly integration with custom model repositories with existing CI/CD tools like GitHub support ML Engineering teams’ automated workflows, while maintaining the DataRobot platform’s governance standards. 

This month, DataRobot also debuts Dedicated Managed AI Cloud on Microsoft Azure. This hosted version of the DataRobot AI Cloud platform is deployed for each customer in a dedicated and separate virtual private cloud that is operated, monitored, and maintained by DataRobot in-house experts. Already available on AWS and Google Cloud marketplaces, Dedicated Managed AI Cloud can now also be purchased on the Azure Marketplace.

Working faster, working with more transparency – those are consistent themes in this month’s DataRobot AI Cloud release.  Learn more how to improve the experience when working with custom models using DataRobot GUI – editable number of execution environments, easier tracking process and update training data when custom model has changed.

Change is happening all around – and impacting your business. Two new DataRobot AI Cloud features help you address change. 

Learn more about Drift Over Time, which helps you with further insights to identify problems and patterns over time. With more information, you can better manage predictions. Deployment Prediction Processing Usage gives you useful details to show which predictions are delayed, why they are delayed, and the time frame so you can make adjustments as needed. 

Today organizations are looking into new ways to apply AI to solve unique business problems—from projecting sales to complex manufacturing development—by adding ML models into the DNA of each business function. The main concern of organizations is how to move fast from experimentation to scaling AI without sacrificing trust and transparency. 

In this release, DataRobot is excited to announce that Time Series Clustering is now available for SaaS users. In addition, DataRobot also focused on improving model observability with large-scale monitoring with Python, data drift monitoring over time, prediction processing stats, and more.

Also this month DataRobot Dedicated Managed AI Cloud is available for public preview. With this model, AI Cloud is deployed for each customer in a dedicated and separate VPC.  By eliminating implementation time and resources, organizations can more quickly apply data engineering, machine learning, decision intelligence, and ML Ops capabilities.

Learn more about  Dedicated Managed AI Cloud and other capabilities only found in the DataRobot AI Cloud platform.