Your AI support ticket triage agent. Route unresolved issues with the attempted fixes.

It is a client-facing agent that classifies the issue against your routing rules and either give a supported answer or escalate the case. It combines request language, issue category, business impact, account details, and previous attempts to produce a routed support case with severity evidence and conversation context. You supply the service rules and records, and the client supplies their own relevant details. The agent has its own page and URL, where the conversation and the current result stay together.

The client explains their situation and supplies the relevant details or documents they are authorized to share. The service as a whole uses request language, issue category, business impact, account details, and previous attempts. Your business supplies its own policies, source connections, and decision rules. The customer is not asked to configure those. A client can answer follow-up questions without understanding your internal systems. If a required source or permission is missing, the agent should explain the resulting limit rather than fabricate the missing fact.

For example, the client can clarify that production is down and update the urgency and receiving queue. The agent keeps the relevant prior context and revises the affected result. In the illustrative preview, the case is assigned to the configured production-support queue. The client can inspect the changed information and continue with the same task.

Use severity and entitlement rules, not sentiment alone. CRM updates and channel replies require verified tool results. Configure this boundary as part of the service, not as a hidden note after a successful-looking result. A pending request, a confirmed external action, and a completed professional outcome must not be presented as the same thing.

Choose the tools that hold the real records or perform the promised action. A diagram shows useful connection roles, not an assertion that those connections are active in a newly created agent. Start with representative sample materials, then connect the live sources required for the actual client task. Verify access permissions and result states before allowing the agent to act on a real account.

Include the agent in your client experience or sell a defined assisted service where the result itself has value. Customers can complete the configured action or continue with your team without restarting the conversation. Define what the client receives, which follow-up is included, and what requires a separate engagement. The page should make that distinction before payment or booking rather than hiding it behind a generic next-step button.

Test a complete request, a missing source, an incorrect input, and a client revision. In particular, test what happens when the client asks to clarify that production is down and update the urgency and receiving queue. Check that the visible result matches the supporting record and that the service respects this boundary. Use severity and entitlement rules, not sentiment alone. CRM updates and channel replies require verified tool results.

No. Morgan's preview is a fictional illustration of support ticket triage. The displayed values, people, records, and statuses are examples. It demonstrates the kind of result your configured service can deliver, without implying that a live account, booking, payment, or other external action has been executed.

It runs on Agentplace. Agentplace is an AI agent platform where the agent gets its own page, talks to your visitors there, and carries the request through to the end instead of handing it to a form. You can open this template and change any step before you publish it.