Article
Shared prediction workflows require consistent control over datasets, jobs, model versions, and results. Without defined access rules, team members may change a configuration, execute an outdated model, or distribute a result without the required review.
Organisation workspaces within the eomer platform provide roles that determine which users can inspect, change, or execute each resource. These roles allow a team to separate model development, review, deployment, and administration responsibilities. The appropriate structure depends on the organisation and the cost of an incorrect change.
The workspace also retains shared access to job history and model versions. Team members can inspect the input configuration, selected model, execution status, and result without separate local records. This shared record supports review and reduces uncertainty about which version produced a prediction.
Job notifications and webhooks pass completed results into downstream workflows. A webhook can notify another service when a job succeeds or fails, while job notifications inform the relevant users. These mechanisms support repeatable processes without continuous manual checks.
For integration work, the dashboard provides equivalent API request examples in Python, TypeScript, and curl. Each example uses the same request structure as the interactive workflow. A team can therefore test a configuration in the dashboard and transfer the approved request to an application or scheduled process.
Together, workspace roles, model records, notifications, and consistent interfaces provide the controls required to move from an individual experiment to a shared production workflow.
