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TryAgent is a human-in-the-loop platform for AI agents that helps teams manage high-stakes decisions within automated workflows. It allows an agent to pause a run when human review is needed, send the decision to the right reviewer with the relevant context, and then resume the exact workflow after a choice is made.
The app is designed for agent review and escalation workflows, including approvals, edits, and rejections for sensitive actions such as refunds, cancellations, or other policy-based decisions. It supports structured routing, SLA-based review handling, signed callbacks, and audit logging so decision-making can be tracked and resumed reliably. TryAgent also includes policy routing, reviewer permissions, tenant isolation, and webhook-based delivery, making it suitable for teams that want to add human oversight to AI agent execution without building a separate review system.
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