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What is AI Tagging? When your AI Agent handles a conversation, AI Tagging reads it and writes a short summary, a sentiment, an intention, a few keyword tags, and one value for each label you define. Use the results to review tickets faster, build customer segments, and read the AI analytics charts.

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How it works

AI Tagging runs only on conversations handled by the AI Agent. Conversations answered only by human agents are not tagged. For each ticket the AI produces:
  • Summary — a short English summary, shown in the ticket detail panel as the AI-generated ticket summary.
  • Sentiment — positive, neutral, or negative.
  • Intention — a short free-text description of what the customer wants. order is the special value for purchase intent.
  • AI tags — 3–5 lowercase keywords describing the conversation.
  • Label values — one value for each label you configure on the AI Tagging page (see below).
The results refresh automatically at several points during the conversation (after the customer’s 2nd, 3rd, 5th, 8th, and 12th message, and so on) and once more when the ticket is resolved. Tagging is not real-time on every message, so a ticket that just started may not show tags yet.
AI Tagging does not consume AI credits. The number of labels you can create is capped per plan: Free 5, Starter 20, Growth 50, and Pro Bundle unlimited. See pricing for plan details.

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Default labels

Every workspace starts with three labels. You can edit or delete any of them.
The Intention chart in AI Agent analytics is built from the intention label. If you delete the label, that chart has less data.

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Create a label

Create labels to track product interest, lead source, complaint type, or anything else you want to know about each conversation.
1

Add a new label

  1. Navigate to AI Studio > AI Tagging.
  2. Click the Add new tag button in the top right corner.
2

Fill in the label

A short name, max 12 characters. This is the name you see in the ticket panel, filters, and analytics.
  • Example: Laptop
Tell the AI what the label means so it knows what to look for in the conversation. A specific description gives more consistent results.
  • Example: “Which laptop model the customer asks about”
Turn this on and enter comma-separated options. The AI picks one of them for every ticket instead of creating its own values. If you leave it off, the AI writes a short free-text value instead.Tag options are not keywords the AI matches in the chat. The AI reads the whole conversation and chooses the option that fits best, even when the customer never types it word for word.
  • Example: MacBook Air, Dell XPS, Lenovo ThinkPad
Saves the label’s value on the customer, so it applies to their future conversations too.
Enable for tags that gather multiple entries over time, such as customer interests.
AI Tagging label form with Label name, Label description, the Tag options switch, and the Add to customer tags and Allow multiple values checkboxes
3

Save

Click Save. The AI includes the label the next time it tags a conversation.

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Example labels

Use tag options when you want clean groups for filters and segments (a fixed list is easier to count). Leave tag options off when the answer is open-ended, such as a product size or a city.

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Where you see the results

  • Ticket detail panel in the bitChat inbox — the AI summary, sentiment, and AI tags for the open ticket.
    • The panel shows an AI tagging card. It shows the intention, sentiment, your label values, Topics, and Key details such as order number, tracking number, SKU, variant, and amount. Click a key detail to copy it, or click Copy summary to ticket notes to add the summary to the ticket notes.
  • Customers list — the Ticket tags filter, and the Ticket tags condition in the segment builder. These work at the customer level and use the latest value of each label for that customer.
  • bitChat analytics overview — the Top 5 AI tags card.
  • AI Tags analytics page — AI tag trends across the period.
  • AI Agent analytics — the Intention chart, built from the intention label.
The inbox chat list does not filter by AI tag, sentiment, or intention. To find customers by label value, use the Ticket tags filter in the Customers list.