Datarobot Doubles Down On ML Ops With Remote Model Lifecycle Management Agents, Automatic Deployment Reports, Centralized Prediction Job Scheduling, And Scoring Code In Snowflake, In Addition To Innovations Across Every Other Product In Its Augmented Intelligence Platform
In its second major release of the year, DataRobot announced several product upgrades to its Augmented Intelligence platform designed to further democratize AI. Building on several enhancements announced at DataRobot’s AI Experience Worldwide last month, these latest additions will enable organizations to drive better business outcomes with AI and further accelerate customers’ time to value.
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“We are in constant communication with our customers regarding the challenges they face when deploying AI, and as a result will tailor our updates based on their unique needs”
With its 7.1 release, DataRobot introduces:
- MLOps Management Agents – DataRobot’s new MLOps Management Agents provide advanced lifecycle management for an organization’s remote models. Management Agents understand the state of any remote model regardless of how they were created or where they are running, and can automate various tasks including the retrieval model artifacts and deployment or replacement of models directly in their environment.
- Feature Discovery Push-Down Integration for Snowflake – Joint DataRobot and Snowflake customers can benefit from the automatic discovery and computation of new features for their models directly in the Snowflake Data Cloud without moving any data, making feature engineering faster, more accurate, and more cost-effective.
- Time Series Eureqa Model Enhancements – DataRobot Automated Time Series now runs its unique Eureqa forecasting models as part of the regular Autopilot process. Eureqa models are based on the idea that a genetic algorithm can fit different analytic expressions to trained data and return a mathematical formula as a machine learning model. With smart feature selection, Eureqa models dramatically reduce complexity and work well with both large and small datasets.
- No-Code AI App Builder – Introduced during the recent AI Experience event, the new No-Code AI App Builder allows customers to quickly turn any deployed model into a rich AI application without a single line of code. AI Apps can be built to help decision makers score new data, perform what-if scenarios, and even run hundreds of simulations to identify the ideal combination of input values to optimize the target outcome.
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“We are in constant communication with our customers regarding the challenges they face when deploying AI, and as a result will tailor our updates based on their unique needs,” said Nenshad Bardoliwalla, SVP of Product at DataRobot. “We’re thoroughly committed to creating a platform that empowers every individual—from the most advanced data scientists to the everyday, non-technical business user—to take advantage of AI. By easing the model lifecycle process and cutting down time to value, this latest round of enhancements gives enterprises the tools they need to better build, manage, and see value from their AI projects.”
The latest platform also includes additional product upgrades, such as:
- Automated Data Prep for Time Series to solve for the most common issues with time series datasets, including gap handling and dataset aggregation.
- Nowcasting for Time-Aware Models to collect critical insights by estimating the present, and yet unknown, conditions of the target variable of interest.
- Automated AI Reports to summarize the most important findings of a modeling project to stakeholders in an easily consumable way.
- Prediction Jobs and Scheduling UI to manage and maintain prediction schedules in one place.
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