Use Cases
AI that answers correctly, and reports you know are used
When Copilot or a Fabric data agent answers from your semantic model, nothing warns you that an answer is wrong. When someone opens a report, Power BI usage metrics do not record what happened next. Each page below starts from one of those questions and ends with what it takes to answer it.
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Copilot gives wrong answers when your semantic model is not ready for it.
AI agents answer badly from a semantic model that looks healthy. BI Pixie assesses its AI Readiness, guides your team through each change, and proves with a benchmark that the answers improved.
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Your Copilot answered correctly last quarter. Does it still answer correctly today?
Semantic models drift, and a wrong AI answer looks exactly like a right one. You run the same benchmark after every change, and BI Pixie shows you the regression before your users find it.
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Power BI usage metrics record that a report was opened, not what happened next.
Power BI usage metrics stop at the page view. BI Pixie captures the clicks, filters, and drill-through that show whether a report is really used.
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Power BI usage metrics do not cover your embedded reports.
BI Pixie tracks clicks, filters, and drill-through inside the reports you embed and publish to web, where Power BI usage metrics do not reach.
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Your Power BI migration is finished. Are people actually using the new reports?
BI Pixie measures whether people actually use the reports you migrated, so the cutover's success is not an assumption.
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If you are looking for the full capability list instead, see what BI Pixie tracks .
See How Your Reports Are Really Used
Replace guesswork with real adoption and engagement data.