Categories and Tracking Rules

How Categorization Works

When Rize detects your active window, it follows this process:

1. Checks your tracking rules for a matching app, URL, or window title
2. Applies the most specific matching rule (e.g., docs.google.com wins over google.com)
3. If no rule matches, the activity is temporarily marked "Miscellaneous"
4. After 2 minutes in Miscellaneous, AI automatically assigns the activity to an appropriate category based on your existing setup
5. View your activity by category in Home > Activity column

Category Settings

Each category has four settings (Settings > Categories):

• Focus Category -- counts toward Focus time detection and improves your focus score
• Work Category -- counts time toward your Work Hours metric
• Idle Detection -- stops tracking after 5 minutes of inactivity in this category (disable for video calls or media)
• Distraction Blocker -- triggers the blocker during Focus sessions when you use apps in this category

Creating Tracking Rules

Go to Settings > Tracking Rules > New Rule to create rules that automatically categorize specific apps or websites:

• Match by app name, URL pattern, or window title keywords
• Assign to any existing category
• Set rules to "Exclude from tracking" for apps you do not want tracked

More specific rules take priority. A rule for figma.com/project-alpha beats a general rule for figma.com.

Initial Categories

When you create your account, Rize generates tracking rules and categories based on your job title. This provides an initial structure for categorization right away.

Overriding Categories

You can override the category for:

• A specific app or website (persistent override)
• A specific time period (one-time override)

Overridden items show a yellow flag indicator in the activity log.

Tips for Better Accuracy

• Add keywords to projects and tasks so Rize matches window titles to the right context
• Connect your task tracker (ClickUp, Linear, Asana) for real task names instead of guessing from raw activity
• Review daily -- corrections teach the AI and improve future suggestions
• Create rules for recurring patterns rather than correcting the same mistake repeatedly