# Quality Assurance Alhena's Quality Assurance tools help you monitor and improve your AI agent's performance by identifying conversations that need review. ## Overview Quality Assurance features allow you to: * **Monitor AI Performance**: Track how well your AI handles customer conversations * **Identify Issues**: Automatically flag conversations that may need human review * **Improve Responses**: Use insights to refine your AI's training and guidelines ## Features ### Smart Flagging Smart Flagging automatically identifies conversations that may have issues, such as: * Unsatisfied customers * Unanswered questions * Potential escalation needs * Response quality concerns This helps your team focus review efforts on the conversations that matter most. ## Getting Started Access Quality Assurance settings in the Alhena dashboard to configure flagging rules and review workflows. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://alhena.gitbook.io/docs/dashboard/conversations/quality-assurance.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.