Legacy access control

Permissions

Note: For newly-created tenants, check the Project-level access control, Managing permissions at tenant level, and Creating a new project and assigning users pages.

In order to perform various actions regarding ML entities, you need certain permissions:

• Display ML logs and view log data - View on ML Logs
• Display projects, datasets, ML packages and pipelines and view their corresponding details - View on ML Packages
• Displays ML skills and allows you to view details on the corresponding ML package (available versions, parameters) - View on ML Skills
• Create a new project, dataset, or pipeline, and upload a new ML package - Create on ML Packages.
• Deploy a new ML skill - Create on ML Skills.
• Update a project, dataset, or pipeline, and upload a new ML package version and view release notes for each version - Edit on ML Packages.
• Update to a new ML skill package version or rollback to an older one - Edit on ML Skills
• Remove projects, datasets, pipelines, and undeployed package versions and packages - Delete on ML Packages.
• Remove ML skills - Delete on ML Skills.
  Note: Permissions are managed in Orchestrator.

For more information on role-based access control, see Project-level access control.

User personas & custom roles

This section treats the subject of user personas which handle AI Center in your company, and the recommended roles to be defined in Orchestrator for each persona.

Data Scientist

In charge of building and uploading the ML models to AI Center. Data Scientists build and then upload ML packages. They can perform this operation from the ML Packages page.

Permissions

• View, Edit, Create, Delete on ML Packages.
• View on ML Skills.
• View on ML Logs.

Process Controller

In charge of deploying models already uploaded by Data Scientists (ML packages), or provided by UiPath® (OS packages), into ML skills. Process Controllers can perform this operation from the ML Skills page.

Permissions

• View, Edit, Create, Delete on ML Skills.
• View on ML Packages.
• View on ML Logs.

RPA Developer

In charge of developing and testing automation workflows; usually does not have access to Orchestrator or the AI Center app. RPA Developers consume the ML skills available on their Robot. These are retrieved from the Orchestrator tenant the connected Robot has been provisioned in.

• View on ML Skills.
• View on ML Logs.

RPA Developers consume deployed ML skills within customized workflows in Studio using the ML Skill activity from the UiPath.MLServices.Activities package. This activity package is only available for Studio v2019.10+ and can only be used by Robots v2019.10+. Read more about it here.