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Approval-based AI workflows
Let AI operate where possible while forcing human approval where the business impact, uncertainty, or policy requires control.
Operational problem
Most AI workflow demos skip the part that matters in production: who approves risky actions, how the decision is explained, and how the team proves what happened later.
Controlled playbook
- AI proposes classification, content, or next action
- Policy determines whether autonomy is allowed
- Approval step shows context and proposed output
- Human reviewer approves, rejects, or edits
- Published playbook version and run details remain auditable
Where control matters
TamePulse is built around bounded autonomy: agents can work inside clear limits, while high-impact execution remains under human control.