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


In the Registry, models are listed as registered models containing deployment-ready model packages as versions. Each package functions the same way, regardless of the origin of its model. From the Registry, you can generate compliance documentation to provide evidence that the components of the model work as intended and the model is appropriate for its intended business purpose. You can also deploy the model to production.

Topic Describes how to
Register a DataRobot model Add a DataRobot model, from Classic or Workbench, to the Registry.
Register an external model Add an external model to the Registry.
Register a custom model Add a custom model from the model workshop to the Registry.
View and manage registered models View and manage registered models and model versions.
Generate compliance documentation Generate compliance documentation for a DataRobot model in the Registry.
View and manage key values View and manage key values for a registered model version in the Registry.
Deploy a registered model Deploy a registered model version from the Registry.
Access global models Access and deploy pre-trained, global models for predictive or generative use cases.
Create custom models Assemble and test model artifacts in the model workshop to deploy custom models through the Registry.
Create custom jobs Assemble custom jobs in the jobs workshop to implement automation for your models and deployments.
Create custom applications Create custom applications in DataRobot to share machine learning projects using web applications, including Streamlit, Dash, and R Shiny.

Updated April 12, 2024