Who can use this feature

Available on monday service

Testing and monitoring show you how your Service AI agents handle requests before and after requesters use them. This article explains how the Service AI Supervisor routes requests, how to test your full setup, how to track AI outcomes on your Tickets board, and how to review performance. Before you test, set up your teams and agents in Get started with monday service AI agents.

Service AI Supervisor

The Service AI Supervisor helps you understand how requests are matched and routed across your Service AI agents. In the left pane, alongside Manage agents and Test, you'll find two collapsible sections: Service Frontliners, listing all the agent teams you create, and Service Ops, where the Supervisor and Service Sidekick live:

When a request comes in, the Supervisor recognizes the request intent and checks whether there is a matching AI agent based on that agent's configured scope. If the Supervisor finds a match, the conversation is assigned to that AI agent. If no matching AI agent is found, the outcome depends on the channel. In portal chat (see Set up knowledge and channels for monday service AI), the Supervisor can first try to help using the portal's resources before routing the request to a human expert. In other channels, the request is routed directly to a human.

Before an AI agent answers, the system checks whether the agent has enough knowledge coverage for the request. If knowledge coverage is too low, the request is routed to a human instead of being answered by AI.

Select Supervisor under Service Ops to review its activity and see how your service flow is set up.

Activity

The Activity tab shows how well requests are being matched for a selected workspace: Matched requests, Unmatched requests, and Match rate. Below that, the activity feed lists each routing decision: the event (such as "Assigned to Agent"), the related ticket, the channel the request came through, the reasoning behind the routing decision (such as "Matched, high confidence"), and when it happened. Filter the feed by workspace, event type, or time range.

Flow

The Flow tab shows a visual map of how your service handles requests for a selected workspace: the channels requests come in through, the board the request is created on, and how the Supervisor routes it. Requests either match an agent's scope and go to In scope, where they're assigned to the matching agent, or fall under No match, where they're assigned to a human expert instead.

Test the full flow

1Select Agents in the left pane, then select Test, located below Manage agents, to simulate the requester experience across your Service AI agents:

2Select a workspace. Portal AI chat is currently the only channel type available for testing. Email and Forms are coming soon.

3Start a conversation to see how the Supervisor routes the request and how the flow behaves end to end:

The left pane also lists your Service Frontliners and Service Ops, so you can jump into any agent's setup or the Supervisor's activity without leaving the test flow.

Each test is saved as its own conversation, so you can return to previous tests, compare outcomes, and continue reviewing them over time. You can also create new tests and delete tests you no longer need.

This is different from the Coverage Test tab inside a single agent. The full Test page is designed for testing across your whole Service AI setup, while Coverage Test is designed for agent-level testing.

Track AI progress

When a request is created through portal AI chat, it appears in the connected Tickets board.

The board includes a dedicated AI Status column that tracks where the request is in the AI flow. The current AI status values are In progress, Pending customer response, AI resolved, and Routed to human.

The AI Status column and your regular workflow Status column are separate. AI Status is system-set and cannot be edited manually. Your regular Status column controls your board workflow and automations.

When AI resolves a request

A request is marked as AI resolved only after the system determines that AI handled it successfully without routing it to a human. This is not decided immediately.

The system waits 24 hours after the last AI response in portal conversations and 72 hours after the last AI response in email conversations before marking the request as resolved.

After a ticket is marked AI resolved, any new requester reply routes the ticket to a human expert. This applies in both portal and email. The AI Status changes to Routed to human, and you can use automations so your regular workflow status reflects that return as well.

What counts as AI resolved?

A request is considered AI resolved only when the conversation stayed with AI, the interaction was meaningful, the requester explicitly confirmed success or implicitly accepted the answer, and there were no negative signals such as dissatisfaction, looping behavior, vague deflection, or abandonment during troubleshooting.

Review performance

Select Performance in the left pane to monitor how your Service AI agents are performing over time. Filter by date range and workspace.

The page opens with three summary cards: AI resolved requests, AI involvement rate, and AI resolution rate, each showing the current figure alongside how much it's changed. The Performance funnel shows how requests move through the flow: total requests, how many involved AI, and the split between AI resolved, in progress, no match, and routed to human.

Further down, review trends over time:

• AI involvement over time and Top AI agents by involvement: which agents are handling the most requests.
• AI resolution over time and Top AI agents by resolution: which agents are resolving the most requests successfully.
• Reasons requests are routed to human experts: a breakdown of why AI handed off, such as low coverage, unable to resolve, or user request.
• Routed to human over time: how that handoff rate trends.

The AI agent performance table lists every agent, its team, request volume, and resolution rate, so you can compare performance across your whole setup. The Documentation performance table shows which knowledge sources are driving resolutions: how often each document was used in a request, how many of those led to an AI resolution, and its resolution rate. Select Improve doc next to a document to strengthen it.

Use this page to understand how often AI is involved, how often it resolves requests successfully, and how often requests still need a human handoff.

Requests dashboards

Below Performance, Requests dashboards links to monday dashboards built on your ticket data, such as an IT Analytics Dashboard, Reporting Dashboard, and any Tickets dashboards set up on your account.

FAQs

How do I test Service AI agents in monday service before requesters use them?

Select Agents, then Test, choose a workspace, and start a conversation. Portal AI chat is the only channel available for testing right now.

What does AI resolved mean in monday service?

The conversation stayed with AI, the requester accepted the answer, and there were no negative signals. The status applies after 24 hours without a new AI response in portal chat, or 72 hours in email.

Can I edit the AI Status column on my Tickets board in monday service?

No. The system sets it. Use your regular Status column and automations to mirror AI progress for requesters.

Where can I see how often Service AI agents hand requests to a human in monday service?

Open the Performance tab and check Reasons requests are routed to human experts and Routed to human over time.

How is the Test page different from the Coverage Test tab in monday service?

Coverage Test checks a single agent. Test checks your whole Service AI setup, including how the Supervisor routes requests.