Focus blocks
Periods where apps, sites, and window context align with meaningful work.
AI time tracker
AI that classifies the work, not just the app.
drifty records Mac activity automatically, then uses context to separate focus, drift, learning, and communication. Choose Local AI when the classification request should stay on your Mac.
The useful signal is not the app name. It is the intent.
YouTube can be a lecture or a drift spiral. Slack can be a launch thread or a distraction loop. Reddit can be research or avoidance. A useful AI time tracker has to look past the label on the window.
drifty focuses on context-aware classification so your reports explain why the day felt focused, fragmented, or scattered.
Early users repeatedly told us the same thing about existing screen-time tools: they do not just want time totals. They want to know what the time meant.
“AI time tracker” can mean very different things.
The useful comparison is not whether a product mentions AI. It is what gets captured, what becomes insight, and where the activity data is handled.
| Tool | Capture | Interpretation | Documented data boundary |
|---|---|---|---|
| drifty | Automatic Mac activity and context | Context-aware focus and drift classification | Complete timeline local by default; Local AI sends no classification request |
| Timing | Automatic app, document, and domain history | Project-oriented review plus optional AI summaries | Local database by default; Sync and AI summaries use its account and cloud services when enabled |
| ActivityWatch | Automatic app and window history | User-authored rule and regular-expression categories | Usage data stays local according to its privacy documentation |
| Rize | Automatic activity capture | AI client, project, and task tagging | Its policy defines tracked activity as User Data retained while subscribed; optional Screen Text can use Vertex AI cloud processing |
Official sources checked September 13, 2026: drifty data boundaries, Timing FAQ, Sync and AI summaries, ActivityWatch privacy and categorization, Rize privacy policy and automatic tracking.
What drifty tries to make reviewable.
The goal is not more raw logs. It is a cleaner explanation of where attention went.
Drift patterns
Repeated checks, rabbit holes, or context switches that pull attention away.
Mixed-use activity
Sessions where the same tool can be useful or distracting depending on the task.
Related drifty pages.
AI time tracker FAQ.
How is drifty different from app-level time tracking?
App-level tracking can tell you which app was open. drifty aims to classify the meaning of that activity, so the same app or site can count differently depending on context.
Does drifty require manual timers?
No. drifty is built around automatic Mac activity capture, with AI classification layered on top for focus and drift analysis.
Can I control how AI classification runs?
Yes. drifty is designed around processing choices such as hosted AI, local classification, and API key-based setup.