AI NativeOperations Lead

Insights that show their evidence — and admit what they missed

Every score reports the share of the window it could actually account for

Insights that show their evidence — and admit what they missed

Do it yourself

Read the insights TimeCampus derives from your own data and, at every step, see the evidence and the coverage behind the number.

0 / 5
  1. Open Work Patterns to see the summary of average focus hours, meeting hours, and productivity, with the insights derived from them.

    You should see: Each insight is typed — a strength, a warning, or a recommendation — and states the observation it came from.

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Related scenarios

Ambitious Consultant

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Let TimeCampus name the project behind each captured hour

Captured activity arrives as raw titles, apps and URLs — attribution is what makes it billable. TimeCampus already scores each event against your project names with a deterministic keyword classifier, then optionally asks an LLM to pick the best match and return a confidence; whichever path wins is recorded next to the event as a suggestion, labelled with the method and the exact model that produced it. The suggested project never becomes the real project until you accept it, and the in-timeline accept/reject controls are the next piece being built.

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Productivity Optimizer

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Weekly suggestions that will never tell you to work more

TimeCampus already runs a weekly pass over your own tracked time and the balance targets you set, and produces a short list of suggestions — no unbroken deep-work block this week, focus ratio down against last week, a life domain sitting well below the share you asked for, time drifting from what you said matters. Each one carries the metrics it was derived from, so you can see exactly why it fired, and each can be accepted, snoozed or dismissed. The invariant that shapes the whole engine: any candidate whose net effect is more work is dropped before it is ever rendered.

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Remote Professional

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Find the hours that quietly leaked out of your week

TimeCampus already buckets the time that went nowhere — the waiting and commuting you logged, activity it could not categorise, and the unaccounted gaps between tracked work — and reports how much of it is genuinely reclaimable. The honest part is what it refuses to count: sleep is never a bucket, and anything you marked as deliberately chosen is excluded from the reclaimable total, so rest is never rebranded as waste. What surfaces is a small number of real hours you can decide to spend differently.

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