Categories that fill themselves in
Every transaction arrives classified. You only correct the misses.
How the app categorizes
Categorization uses a 5-layer pipeline, in priority order:
1. File metadata β if your bank includes a category in the CSV, it's used directly 2. Your rules β ones you created manually or approved 3. Merchant database β 440+ known merchants by country 4. Learned patterns β corrections you made before (β₯2 times = pattern) 5. Keyword classifier β last-resort heuristic
Default categories
The app comes with 36 hierarchical categories (14 parents + 22 children). You can use them as-is, customize them, or start from scratch.
Automatic rules
When the app detects you always categorize the same merchant the same way (β₯3 times, β₯80% consistency), it suggests creating a rule. Rules are created disabled β you approve them before they apply.
Machine Learning (on-device)
Three models trained with 3,197+ samples and 7,680+ phrases:
Everything runs on your device. No data ever leaves it.
Financial DNA
The app observes each category's behavior and builds a probabilistic profile:
If it detects a category isn't behaving as you classified it, it alerts you with an insight.
