Triage Agent Summary Dashboard

The Triage Agent Summary dashboard gives you a complete view of how Triage Agent is performing across your service desk — from the moment a ticket arrives to how it ultimately resolves. It answers three questions in one place: how much the AI is actually doing, how well it’s doing it, and what people think of the results. Open it from Thread admin → General → Analytics.

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What this dashboard answers

• What share of tickets is Triage Agent resolving with no technician involvement?
• Where do tickets drop out of the triage flow, and into what?
• Is zero-touch performance improving month over month?
• Which boards are getting the most value from triage, and which need configuration work?
• What are technicians and customers saying about the AI’s work?

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Filters and time windows

A filter bar at the top applies globally — every chart, table, and metric on the page updates together:

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What’s on the dashboard

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Session overview

Headline metrics for the selected period, each carrying a status badge — on target, below target, or high — so a problem is visible without reading the numbers:

• Total sessions and unique tickets triaged
• Zero-touch rate — resolved by the AI with no technician involvement
• Assisted handoff rate — triaged by the AI, then routed to a technician
• Intervention rate — a technician had to step in or reply directly
• Blocked rate — sessions that failed to complete, through timeouts, errors, or rejected approvals
• AI first reply — median time to the AI’s first response
• Average reply time and feedback count

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Triage flow

A Sankey diagram showing how tickets move through triage, with four views you can switch between: Bar width represents ticket volume, so the bulk of your traffic and the places it drops off are both visible at a glance.

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Bucket breakdown

The same outcome buckets as a table — session counts and each bucket’s share of total volume, with proportional bars for quick comparison.

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Outcome trend

A 12-month line chart tracking zero-touch, closed, and open outcomes month over month. This is where you see whether AI performance is genuinely improving or just holding.

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Board performance

Outcome rates — zero-touch, closed, open — broken out by service board, so you can tell which queues are benefiting and which need a configuration adjustment.

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Feedback feed

A single chronological feed of every rating on the AI’s work, from both audiences:

• Technicians — routing quality ratings
• Customers — reactions to AI-generated notes

Filter the feed by source (Customers, Technicians) or by type (Routing Ratings). A summary bar shows total ratings, positive rate, and average routing score.

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Metric definitions

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Things to watch

• Sessions and unique tickets differ. A ticket can be triaged more than once, so read rates against the denominator the tile names.
• A high intervention rate isn’t automatically bad early in a rollout — technicians stepping in is how you find the intent gaps. It’s a problem when it stays high.
• Blocked sessions are a configuration signal, not a quality signal. Look at approvals and integration setup before you look at the AI.
• The 90-day default hides a new rollout’s progress. Narrow the date range when you’ve just changed intents or settings.
• Data refreshes daily, so today’s sessions generally appear tomorrow.

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Next steps