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Opening a ticket from any QA list puts you on the same screen: the evaluation on the left, the ticket itself on the right, and a thin top bar that moves you between tickets. Everything a reviewer needs to agree or disagree with a score is on it. The ticket QA workspace, with the AI review and criterion reasoning on the left and Details, Timeline, and Conversation on the right

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The layout

The top bar holds the back arrow, the review tabs, and Previous / Next. Those two buttons walk the list you arrived from, in the order it was in, so a filtered list works as a queue: filter down to what you want to review, open the first one, and work forwards. The left panel is the evaluation: a headline score, then one tab per agent on the ticket, then a card for each criterion on the scorecard. The right panel is the ticket: Details, Timeline, and Conversation, each of which collapses. On a narrow window it hides entirely rather than shrinking, and a Conversation details button appears in the top bar to bring it back.

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Reading the score

Under the heading Quality score, a coloured tile carries the number and a Summary beside it gives Rulebase’s account of what happened on the ticket in a few sentences. Red, amber, and green come from your organization’s risk thresholds rather than a fixed cutoff, so 44 can be red in one organization and amber in another. Click the small information icon on the tile to break the number down. The tooltip lists every evaluator and scorecard that contributed, which is the fastest way to tell whether the headline is one AI score, an average across two agents, or a manual score sitting on top of an AI one.
A ticket handled by more than one agent gets one tab per agent under the score tile, and each agent is scored separately. The tab you are looking at is one agent’s evaluation, not the ticket’s. Hover a tab to reveal a ⋮ menu with Add to coaching, which sends this ticket into that agent’s coaching queue.
Under the tabs, a row reads Priya Nair's score • Support QA and repeats the score for that specific agent and scorecard. If the same agent was scored against more than one scorecard, the scorecard name becomes a dropdown.
  • Auto-Zero — a criterion marked as an auto-fail was failed, so the whole scorecard result is zero regardless of what else went well.
  • A score badge with a tooltip — a score cap was applied, and the tooltip says why.

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Reading the reasoning

Each criterion is a card: the question from the scorecard, the outcome as a pair of badges (Fail and 0 / 30), and beneath it the AI’s explanation of how it reached that outcome against this specific conversation. A criterion card showing the question, a Fail badge with the score, and the AI's written reasoning Review the explanation, not just the score. If it cites a moment that did not happen, or misses one that did, that is a scoring error, and the thumbs up and thumbs down on each card are how you say so. Give feedback on AI QA covers what happens next. A View explanation control appears on cards where there is more underneath: the justification the AI selected, or an answer drawn from your knowledge base with the sources it used. Not every card has one, and its absence just means the reasoning above is the whole story.
Scan the criterion cards before you read the transcript. You will read the conversation differently once you know which two moments are in dispute, and it takes half the time.

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The ticket panel

Details carries the facts you need to judge context or to go and look at the original: the customer, ticket status, the assignee, when it started, and the ticket ID as a link out to the source help desk. View more expands the rest: when the ticket was evaluated, when Rulebase imported it, and any custom fields that came across from your help desk. The Details panel showing customer, status, tags, ticket ID, assignee, and start date The Tags row is editable: the + applies an existing Rulebase tag or creates one on the spot. The Tags filter is only offered on an Interactions view, not on the QA Tickets view, so tag now and filter there. Timeline is the review history rather than the ticket history: who this ticket was assigned to and when, and any contests raised against its scores. Conversation is the exchange itself, customer messages and agent replies in order.

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When there is no AI score

Not every ticket has one, and the workspace tells you which case you are in rather than showing a blank panel. Evaluation skipped comes with the specific reason, often that the ticket is not closed yet, or that a linked ticket in the thread is still open. Evaluation failed means it ran and errored. Evaluation scheduled means it is queued. No QA evaluations means nothing was ever attempted. Each of those states offers a button to move it along: Try again after a failure or a skip, Run now on a scheduled evaluation, and Request evaluation where nothing has run. Why wasn’t my ticket evaluated? covers the reasons in depth. None of it stops you scoring the ticket yourself. The + beside the review tabs adds a Manual evaluation tab and starts one, whether or not the AI got there first. See Perform a manual evaluation.