AI Workflows
AI Workflows let you turn recurring document-grounded work into controlled, repeatable AI processes. Instead of re-running the same prompt manually, you can define the workflow once, run it on demand or on a schedule, and keep a governed record of the result.
What AI Workflows Are Good For
AI Workflows are especially useful when you need to:
- summarize or review approved documents the same way every time
- chain multiple AI steps into one operating procedure
- trigger work from schedules, uploads, or webhooks
- keep a reviewable record of each run
- benchmark and improve workflow quality over time
Core Workflow Building Blocks
An AI Workflow can include:
- prompt steps
- loop or container steps
- structured outputs
- output templates
- workflow variables
- trigger variables
- sub-workflows
- model selection
- optional web access, when allowed
Scheduling and Calendar Visibility
AI Workflows can run on demand or on a recurring schedule.
Use Workflow Calendar for a schedule-first view of upcoming runs, scheduled activity, and recent workflow jobs.
Triggers and Operational Use
Workflow jobs can be started from several paths, including:
- manual creation
- recurring schedules
- webhook triggers
- upload-triggered flows
- sub-workflow execution from another workflow
These patterns make AI Workflows useful as operational AI, not just one-off prompting.
Benchmarks and Human Checkpoints
Clear Ideas also supports workflow quality and control features that help teams make AI execution more dependable:
- AI Workflow Benchmarks for evaluating quality over time
- human approval or human-in-the-loop checkpoints where review is required before work proceeds
Use these controls when consistency, reviewability, or compliance matters more than raw automation speed.
Governed Workflow Records
Workflow definitions, jobs, and related outputs are part of Clear Ideas' governed AI record. That makes it easier to review what ran, when it ran, and what it produced.
See Governed AI Records and AI Workflow Jobs.