Beyond rule-based automation
Traditional automation breaks the moment a step needs interpretation — reading a document, weighing options, or writing a reply. An AI workflow handles those steps because the agent reasons over the inputs instead of just matching triggers to actions.
You compose a workflow from steps the agent executes in order, branching on what it finds. Each run is durable and observable, so you can see exactly what happened and where a human signed off.
What it automates
Anything that strings together research, content drafting, data lookups, and routing across multiple tools — reporting, onboarding, intake triage, follow-ups, and recurring operational checklists are all good fits.
Workflows can run on a schedule, fire from an event, or kick off on demand. Where a step carries risk, the agent proposes ranked options and waits for a person to approve before continuing.