Start, stop, and manage the lifecycle of your AI teams.
Deploying a Team
Each team runs in its own isolated environment. Here's how the lifecycle works.
Team Statuses
| Status | Meaning |
|---|---|
| Draft | Team is not yet fully configured |
| Stopped | Configured but not running |
| Creating | Environment is being set up |
| Running | Live and processing messages |
| Error | Deployment failed |
| Archived | Permanently deactivated |
Starting a Team
- Make sure the team has all required blocks configured
- Make sure your company has a positive balance
- Click Start on the team detail page
- Wait for status to change from "Creating" to "Running" (usually 30-60 seconds)
Your team is now live and ready to work.
Stopping a Team
- Click Stop on the team detail page
- The environment shuts down
- Infrastructure costs are calculated and deducted
- Agent memory is preserved for next start
Stopping a team does not delete agent memory. When you start it again, the agents can pick up where they left off.
Archiving
If you no longer need a team:
- Stop the team first (if running)
- Click Archive
- The team is hidden from your active view
Archived teams can be unarchived later if needed.
Costs While Running
While a team is running, you're billed for:
- Infrastructure — $0.02/hour for the running environment
- LLM usage — per-token costs based on the models used
Both are deducted from your company balance in real-time. See Usage Tracking for details.
If your company balance reaches $0, all running teams in that company will be stopped automatically.