Automatic categorization

Automatic investment balance categorization works to catch issues that slip your rules or to categorize entire breakdowns without rules.

Automatic categorization is currently in closed beta.

What is automatic categorization?

AI categorization works alongside your existing rule-based categorization system. When you toggle it on for a breakdown, Swarmia first applies any categorization rules you've defined. Then, for any issues that remain uncategorized, AI analyzes each issue's description, linked issues, and other metadata to determine the most suitable category based on your category descriptions.

To use AI categorization, you'll need to add descriptions to your investment categories. The more detailed and clear your descriptions, the better the results. See our writing guide.

Once enabled, you can review how issues have been categorized in the categorization view to ensure they've been assigned correctly. You'll see an icon (✨) next to the category to indicate it has been categorized by AI, and you can hover to review the reasoning.

How to get started

You can find the toggle to enable automatic categorization for an investment balance breakdown in the breakdown settings, between your defined categories and the Everything else category.

Writing good category descriptions

Descriptions matter for the accuracy of the automatic categorization, so it's beneficial to spend some time thinking about good descriptions.

Why descriptions matter

Category descriptions serve two audiences. The first sentence should be written for people reading your categories. The remaining content serves as a prompt for the AI categorization system to determine where work items belong.

Previously, category descriptions were written for internal team members who already understood your context. For AI categorization, you need to be more explicit about your company and development work.

Think of it like onboarding a new employee: provide enough context so they can make quick, accurate decisions. This approach improves both AI accuracy and internal clarity.

Writing effective descriptions

Start by observing how your team writes issues. Pay attention to naming conventions and what information is typically included. Use these patterns when writing your category descriptions.

For the AI portion, include decision-making guidance such as:

• Positive and negative examples

• Relevant keywords

• Specific instructions on edge cases

This additional context helps the AI understand not just what the category is, but how to identify work that belongs in it.