TryAgent.ai

I built TryAgent after wiring the same flow into a couple of agents: the agent hits something it shouldn't decide alone, and you need a human in the loop — fast, to the right person, with a record. Pausing the agent turned out to be the easy 10%. The other 90% was the operations around the pause: routing to the right reviewer, an SLA so it doesn't hang forever, a safe default when no one answers, capturing a clean structured decision instead of a freeform reply, and an audit trail compliance would actually accept. Then handing the decision back to the workflow so the run continues. So TryAgent is that layer — think incident response / on-call, but for the decisions AI agents escalate. It drops into a LangGraph interrupt, and ships TS + Python SDKs. Would genuinely love feedback on the routing + timeout model. What does "escalate to a human" look like in your agents today?