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A ticket label is something you want to track across conversations, such as Angry customer or Churn risk. The AI Agent reads your list and labels every conversation against it, so you can filter, sort, and report on qualities no other filter captures. Labels live in one workspace. Each workspace keeps its own list and labels only its own conversations.
Only Admin users can create, edit, or delete labels. Any agent can change the labels on a single conversation from the ticket details panel.

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How labeling works

The description you write is the instruction the AI Agent follows. It re-checks the conversation against your whole list on every customer-visible message, so labels keep up as a conversation develops. Your decisions outrank the AI Agent’s:
  • A label you add by hand is never removed by the AI Agent.
  • A label you remove by hand is never re-applied by the AI Agent.
A workspace with no labels is the off switch. Until you create the first label, nothing is classified.

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Create a label

1

Open Ticket labels

Go to Settings, pick your workspace, and open the Ticket labels tab.
2

Create

Click Create label, then pick a color and enter a name.
3

Describe when it applies

Fill in When should this label be applied?. Write the criteria the AI Agent should judge the conversation on.
4

Test it

Click Test to try the description on real conversations before you save.
5

Save

Click Create label. New conversations are labeled from here on.
Label names are unique within a workspace. Reusing a name tells you the name is taken.

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What to put in the description

Write criteria, not a definition. “The customer expresses anger: shouting, capital letters, insults, or threats to escalate” beats “angry customers”. The AI Agent judges the conversation against your sentence, so name the evidence you would look for yourself.

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What the AI Agent can see

The classifier reads the conversation’s whole timeline, not just the customer’s words. Anything in this table is fair game in a description. The classifier sees only the conversation it is labeling. It cannot read the customer’s other tickets, your reports, or anything outside the timeline.

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Examples

Label what a filter can’t already tell you. Status, team, channel, assignee, and resolution are filters of their own, and the Specialist already records which flow ran. Labels earn their place on judgment calls: sentiment, intent, risk, and quality.
One label, one idea. Angry customer and Churn risk sample cleanly on their own, while a combined Unhappy or leaving label is hard to write criteria for and harder to act on.

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Test a label before you save it

Test runs your draft against the workspace’s last 25 conversations and shows what it would have matched. Results stream in one conversation at a time:
  • A green check means the label would apply.
  • A grey cross means it would not.
  • The eye icon opens that conversation in a new tab.
Nothing is saved by a test run, and no labels are applied to those conversations. Test as often as you like while you refine the wording, on a new label or an existing one.
Sampling calls the AI once per conversation, so a run takes a moment to finish. It starts only when you click Test, never on every keystroke.

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Edit a label

Open a label from the table to change its name, color, or description. Changes take effect on the next classification, so conversations already labeled keep their labels until something new happens on them. Renaming a label keeps it on every conversation that carries it. Rewriting the description changes what it matches from that point on. It does not re-label history.

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Delete a label

Deleting a label removes it from every conversation that carries it, and from the filters of any saved view that uses it. A view that filtered on that label alone shows all conversations again. This cannot be undone.
The conversation history keeps the record. Timeline entries that mention the label stay readable after it is gone.

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Limits

The workspace limit keeps classification accurate and affordable. The whole list travels with every conversation the AI Agent classifies, so a long list costs more and decides less reliably. At 30 labels, Create label is disabled until you delete one. On a conversation already carrying 5 labels, the remaining labels are greyed out in the picker, and your own choices keep their slots before the AI Agent’s.

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Change the labels on a conversation

Open a conversation and use the Labels field in the details panel.
1

Open the picker

Click the + button next to the label chips.
2

Toggle labels

Check the labels that belong on this conversation and uncheck the ones that don’t.
3

Close the picker

Your changes are saved when the picker closes. A session of edits becomes a single timeline entry, not one per label.
The conversation timeline records every change and who made it, so “AI added a label: Churn risk” and “Nina removed a label: Churn risk” both stay visible. That history is how you tell an AI label from a corrected one.

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Filter and report by label

Once a workspace has labels, they show up across the ticket list:
Pair a label filter with Resolution status to see how one kind of conversation actually ends. A label the AI Agent rarely resolves is usually pointing at a knowledge gap or a missing action.

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See also