AI assisted Checkly features

Checkly AI is not one feature, but a set of features that use AI to enhance your monitoring and testing capabilities. Currently, you can use AI in the following parts of the product:

On each failed Playwright-powered check result, Checkly AI analyzes the traces, script code, screenshots and script code to provide you with a detailed analysis of the failure. This includes:

• End-user impact: Checkly AI analyzes the failure and provides you with a list of impacted users and features. The text used is generated by AI and can be enriched with organisation-specific domain knowledge using the Tag description editor the AI settings screen.
• Step summary: Checkly AI summarizes the steps in the check script, making it easier to understand what the check is doing and where it failed.
• Root cause: Checkly AI analyzes the failure and provides you with a root cause analysis, helping you quickly remediate the issue.

Using the Tag Description Editor, you can add custom descriptions to your tags. Checkly AI uses these descriptions to provide more context and insights into failures and the impact on user groups, features and applications.

This is very useful for organizations with specific domain knowledge and terminology embedded in their tags. For example, a tag like feat:checkout can be enriched with a description like “This tag is used for the checkout feature of our e-commerce application, which allows users to purchase products online.”

On each Playwright error, Checkly AI provides you with an error explanation. This includes:

• A general explanation of the error.
• A suggestion on how to fix the error with a code snippet.
• A (set of) link(s) to the Playwright documentation for the error.

Last updated on June 6, 2025. You can contribute to this documentation by editing this page on Github