Skip to content

On-premise users: click in-app to access the full platform documentation for your version of DataRobot.

AI Platform releases

This page provides announcements of newly released features available in DataRobot's SaaS single- and multi-tenant AI Platform, with links to additional resources.

May SaaS feature announcements

May 22, 2024

With the latest deployment, DataRobot's AI Platform delivered the new GA and preview features listed below. From the release center, you can also access Self-Managed AI Platform release notes.

May features

In the spotlight: Asset migration

Deployed last month, DataRobot allows you to transfer projects and notebooks created in DataRobot Classic to DataRobot NextGen. This is how.

Video: Asset migration

Preview documentation.

Feature flag OFF by default: Enable Asset Migration

The following table lists each new feature:

Features grouped by capability
Name GA Preview
Generative AI
Anthropic Claude 2.1 now available ✔*
Predictions and MLOps
Batch prediction output support for SAP HANA JDBC connector
Create schedules for Codespaces
Python client v3.4
DataRobot REST API v2.33
Deprecations and migrations
DataRobot account portal deprecation

* Premium feature


Anthropic Claude 2.1 now available

Now available on SaaS, the DataRobot GenAI playground introduces Anthropic Claude 2.1 as an LLM option when constructing LLM blueprints. Claude Anthropic is an open-source generative LLM that is the base model that powers many chatbots, billing itself as the “ethical alternative.” It is available in new experiments and also can be added to existing playgrounds.

Batch prediction output support for SAP HANA JDBC connector

DataRobot now supports JDBC write-back when you configure a JDBC prediction destination using a SAP HANA data connection through the Job Definitions UI or the Batch Prediction API.

For a complete list of supported output options, see the data sources supported for batch predictions.


Create schedules for codespaces

Now available as a preview feature, you can automate your code-based workflows by scheduling notebooks in codespaces to run on a schedule in non-interactive mode. Scheduling is managed by notebook jobs, and you can only create a new notebook job when your codespace is offline. You can also parameterize a notebook to enhance the automation experience enabled by notebook scheduling. By defining certain values in a codespace as parameters, you can provide inputs for those parameters when a notebook job runs instead of having to continuously modify the notebook itself to change the values for each run.

Preview documentation.

Feature flag ON by default: Enable Codespace Scheduling


Python client v3.4

v3.4 for DataRobot's Python client is now generally available. For a complete list of changes introduced in v3.4, view the Python client changelog.

DataRobot REST API v2.33

DataRobot's v2.33 for the REST API is now generally available. For a complete list of changes introduced in v2.33, view the REST API changelog.

Deprecations and migrations

DataRobot account portal deprecation

In this release, the DataRobot account portal is deprecated and removed. This deprecation updates the appearance and selection of DataRobot user profile settings, as shown below.

All product and company names are trademarks™ or registered® trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.

Updated March 26, 2024