Deploying publishes your workflow so it can be run by your team or called through the API. You edit freely on the canvas, but only a deployed version serves real traffic.Documentation Index
Fetch the complete documentation index at: https://docs.platform.aiplanet.com/llms.txt
Use this file to discover all available pages before exploring further.
What a deployment is
A deployment is a versioned snapshot of your workflow at the moment you deploy it. Editing the canvas afterward does not change a deployment — your live version stays stable until you deploy again. This means you can keep improving a workflow without disrupting whatever is already running in production.Deploying
Save your workflow
Make sure the builder header shows your workflow as saved. The Deploy control is disabled while you have unsaved changes.
Click Deploy
Use the Deploy control in the builder header. You’ll be asked for an application name — this identifies the deployment. The platform then creates a new deployment version.
The active deployment
Each time you deploy, a new version is created (v1, v2, and so on). One version is active at a time — that’s the one that actually runs when the workflow is triggered.
From the version selector you can see every version and switch which one is active: select an earlier version to load it back into the canvas, then activate it. This lets you roll back to an earlier version if a new deployment doesn’t behave as expected.
Deploying again doesn’t delete earlier versions. Your deployment history is kept so you can always return to a known-good version.
Stopping a deployment
If you need to take a workflow out of service, use Stop Deployment in the builder header. This deactivates the active deployment — the workflow can no longer be triggered by your team or through the API until you deploy again. Your version history is retained.After deploying
A deployed workflow can be run in two ways:By your team
Through the platform interface.
Through the API
Triggered from your own applications.