DataRobot Touts New AI Cloud Solutions
June 10, 2022
has focused a decade of innovation to make artificial intelligence
accessible to all businesses, and accelerate AI into production.
Today, DataRobot is one of the most widely deployed AI platforms in
the world, delivering over 1.4 trillion predictions for leading
Bias Mitigation capabilities to reduce business risk, delivering a higher level of bias prevention by automatically identifying and adapting models before they reach deployment to mitigate bias and assure fairness.
Integrated Code-First Notebooks providing data scientists access to all necessary tools and resources to do exploratory, code-centric work. DataRobot is announcing the preview of Code-First Notebooks that are fully integrated in DataRobot AI Cloud, and bring together our capabilities from Zepl to deliver a purpose built environment for expert Data Scientists.
Enhanced predictive AI Apps for business users, adding geospatial capabilities. Now geospatial data is integrated in DataRobot’s No-Code AI Apps, allowing users to deliver unique insights by location and markets for even more targeted business decisions.
Ensure Enterprise Trust:
Management agents for remote deployments, supporting the distributed needs of enterprises. This expanded capability supports complex use cases where monitoring and managing models is necessary across a range of services, deployed in multiple clouds, and all with the security and governance of a user’s current systems.
Automated compliance documentation for all models, even those built outside of DataRobot. This enhanced capability brings greater efficiency and governance to all models, including highly regulated industries. Organizations can now rapidly generate compliance documentation while centrally managing governance across their entire model portfolio.
Expanded support for proven DevOps practices with integration to GitHub Actions to automate ML workflows in line with proven CI/CD principles. By integrating AI Cloud into CI/CD practices teams can operate more efficiently, and bring AI to production faster and with more consistent levels of quality.
in part to rapidly maturing AI development tools and best practices,
the enterprise AI market is quickly reaching critical mass and
adoption is approaching self-sustaining levels. This is further
supported by a recent Omdia study that found 25% of enterprise
buyers are currently looking to scale AI projects across multiple
business units or functions,” said Bradley Shimmin, Chief Analyst,
AI platforms, analytics, and data management at Omdia. “Building on
this kind of momentum, however, will demand that practitioners look
beyond the operationalization of basic ML workflows to also view
those workflows as an integral part of the business itself, fully
embracing business users, speeding time to value, and minimizing
business risk through tools supporting transparency, trust, and