Manual
Reusable goal on demand
Start a prepared agent goal when needed without rewriting the task each time.
- Saved agent goal
- Start on demand
- Result as a thread
AI automations
Run recurring AI tasks on a predictable schedule.
2342.ai can execute saved agent goals manually, at intervals or through a webhook. Every run creates a result thread; status, errors and usage remain visible in the product.
What is implemented today
One agent goal, three triggers and a visible result.
An automation contains a reusable agent goal and starts manually, after an interval or through an incoming webhook. The result is stored as a thread. Completion can optionally be sent to a webhook; activity status and mobile notifications report on the run.
workspace.open()
mode.private_or_business()
knowledge.connect()
automation.run()
budget.meter_usage()
Interval
Recurring execution
Interval automations become due again after the configured duration and are executed.
- Configurable interval
- Next run visible
- Status and errors visible
Webhook
Start from another system
An incoming webhook can trigger the run; an optional destination webhook receives the result.
- Webhook trigger
- Optional result webhook
- Usage budget checked
Automation ideas
Recurring AI work should not need a fresh manual start every time.
Write the agent goal
Define the reusable instruction the model should execute.
Choose a trigger
Configure manual start, an interval or an incoming webhook.
Review the result
Thread, run status, errors, usage and optional webhook delivery remain visible.
Which triggers are available?
An automation can start manually, after a configured interval or through an incoming webhook.
Does it automatically search Drive or SharePoint?
No. Knowledge sources are a separate feature. The current automation executes its saved agent goal; automatic file search is not promised here.
Where does the result go?
Every run stores a result thread. The result can optionally also be delivered to a destination webhook.