Teams & Workflows
A team in CloudAxis is a set of AI specialists that Cloudia designs from a plain-language description of your workflow, then deploys — together or one at a time — as scheduled duties that hand off to each other.
Describe the workflow to Cloudia
Open a chat with Cloudia, your AI chief of staff, and describe the outcome you want in plain language — for example, "watch our support inbox, triage new tickets, and draft first replies for anything urgent." Cloudia asks a few clarifying questions about volume, timing, and how hands-on you want to be, then proposes a team built for that workflow.
What a team proposal includes
Cloudia's proposal lays out three things you can review before anything is created:
- Roles — which specialists to hire and what each one is responsible for.
- Schedules — when each specialist's duties run.
- Hand-offs — the order steps run in, and which specialist picks up after which.
Review before you deploy
Nothing is hired or scheduled until you confirm the plan. Read through the proposed roles, schedules, and hand-off order, and adjust anything you'd change — swap a specialist, move a schedule, or drop a step you don't need — before deploying.
One-click deploy, or step by step
Once you're happy with the plan, Cloudia shows a deploy card with two ways to bring the team on:
- Deploy all at once — every specialist is hired, every duty is scheduled, and the hand-off chain between them is wired up in a single confirmation.
- Deploy one specialist at a time — hire and test the first specialist, refine its duty if the first runs need adjusting, then add the next specialist once you're satisfied. This is useful when you want to see a step run cleanly before committing to the rest of the chain.
How the chain runs once deployed
After deployment, steps run in sequence: a specialist hands off to the next specialist in the chain after it finishes a clean run. You don't have to trigger each step yourself — a successful run is what starts the next one.
If a step fails, the chain stops right there. It doesn't skip ahead to the next specialist and doesn't quietly retry the rest of the pipeline — you're notified so you can look at what happened before anything downstream runs on incomplete or bad input.
Adjusting a team later
Teams aren't fixed once deployed. Add another specialist, change a schedule, or rewire which step hands off to which by describing the change to Cloudia, or by editing the team directly — the same way you built it in the first place.