Choose a starting point
Start from a catalogued platform event, a cron schedule, an API call, Studio, or another pipeline. The input arrives as a typed value that seeds the graph.
Bosca Pipelines
Pipelines are Bosca's visual automation: stored transform graphs that accept a platform event, reshape it, branch on conditions, and act — enqueue a job, send an email, post to Slack, call a webhook — without writing or deploying code.
How it works
Start from a catalogued platform event, a cron schedule, an API call, Studio, or another pipeline. The input arrives as a typed value that seeds the graph.
Drag nodes from the palette onto the canvas and connect them: transforms reshape the data, routes branch on conditions, actions do something with the result. The inspector configures whatever is selected.
Flip the Active switch and the pipeline runs on the platform's background job infrastructure every time its event fires. Every run is logged with its outcome, timing, and any error.
What makes it powerful
When the logic is "take this event, shape it, decide, act", a pipeline expresses it as a diagram — with the execution engine, durability, and audit trail handled by the platform.
Transforms, conditions, and actions wired on a canvas — a diagram anyone on the team can read and edit.
Run on matching platform events or a standard cron schedule, with the same durable history and limits either way.
Values keep their types as they flow. Input slots declare what they accept, and the editor refuses connections that don't fit.
Trace a sample event through the saved graph. Action nodes record what they would do — and do nothing.
Delay, Wait Until, and job waits park a run durably and resume it later. A restart doesn't lose it.
Run Pipeline, For Each, segment-wide fan-out, and Dispatch Event build large automations out of small, reusable graphs.
Describe the automation in conversation, refine the result with Kit, and continue visually in the graph editor.
Webhook URLs and signing keys are encrypted secrets, referenced by name and resolved only at execution time.
Outcome, timing, and errors for every run — plus a live view streaming node-by-node progress as it executes.
Shaping data
Events are intentionally lean — an id, a name, a timestamp. Fetch nodes resolve the full entity, and a JSONata node reshapes it into exactly what the receiving end expects. The inspector's workbench previews the expression against a sample input without leaving the editor.
$eventCreated is bound to the run's occurrence timestamp in every expression.{
"profileId": id,
"displayName": name,
"occurredAt": $eventCreated
}Dry runs
A dry run feeds a sample event through the whole graph exactly as a real run would — except action nodes record what they would do instead of doing it. The node-by-node trace shows every value on every edge, so you see the shape of the data before you flip the pipeline to active.
Go deeper
A three-pane graph workspace with typed connections and versioned saves.
Transforms, routes, actions, and the nodes your domains contribute.
Trace a sample event through the graph before anything goes live.
Event-triggered, durable execution with every run logged.
Every subsystem publishes its events to one catalog, and every catalogued event can trigger a pipeline — content publishes, profile changes, task transitions, comments. The docs cover the editor, the node vocabulary, and the execution model end to end.