With its first platform release of the year, DataRobot continues to advance customers on the path to becoming AI-driven enterprises
DataRobot today unveiled significant upgrades to every product in its enterprise AI platform. These enhancements, created based on critical input from customers, are designed to optimize the value seen through AI deployments and enable organizations to drive better business outcomes with AI.
Notable enhancements include:
- MLOps remote model challengers, which allow organizations to challenge any production model – no matter where it is running and regardless of the framework or language in which it was built. By analyzing how challenger models perform versus the current champion model on the exact same production data, companies can easily determine which model is best for them now or at any point in history – helping inform decisions about whether to keep or replace the current champion model, ensuring they always get the most accurate predictions possible.
- Choose your own forecast baseline, which lets companies compare the output of their forecasting models with predictions from DataRobot’s Automated Time Series product. Through this capability, organizations can feel confident that DataRobot is forecasting as expected and understand if DataRobot’s models are more or less accurate than their existing ones so they can leverage the best possible forecasts.
- Visual AI image augmentation, available through DataRobot AutoML,which creates new training images from a company’s dataset by intelligently replicating and transforming the original images. As a result, organizations can improve the overall accuracy of their image models while reducing the need to manually capture and label new images, which is time-consuming and expensive.
- Enhanced prediction preparation. DataRobot’s visual data prep capabilitiesempower organizations to quickly and easily prepare their data for model training. In release 7.0, customers can now use visual data prep to more easily score new data from models already deployed. This is because DataRobot’s Data Prep tools work seamlessly within its end-to-end platform, enabling companies to easily secure scored data and prediction explanations from any deployed model – ensuring full transparency and trusted AI.
The latest platform also includes additional product upgrades, such as:
- AutoML automatic bias and fairness testing is enhanced and now generally available.
- Data Prep now contains enhanced improved APF monitoring, automatic date transformations, and a new elastic Spark-based infrastructure.
- Automated Time Series offers monotonicity constraints and a new unsupervised anomaly over time model comparison feature.
- MLOps now provides support for connecting to GitHub Enterprise and Bitbucket Server, in addition to offering new features that help organizations more effectively manage production models.
“We are committed to helping enterprises experience the greatest value from their AI models,” said Nenshad Bardoliwalla, SVP of Product at DataRobot. “Through ongoing engagement with our customers, we’ve developed an intimate understanding of the challenges they face, as well as the opportunities they have, with AI. Our latest platform release has been specifically designed to help them seize the transformative power of AI and advance on their journeys to becoming AI-driven enterprises.”