# EnateAI - 'Thank You' Email Evaluation ## Overview Our 'Thank You Email Evaluation' pattern, available in [Marketplace](https://docs.enate.net/enate-help/builder/builder-2021.1/integrations-marketplace) in Builder automatically detects whether incoming emails to a resolved work are just simple 'thank you emails', and if so then have them automatically moved back to a state of 'resolved' without agent users having to manually perform such repetitive checks. Importantly, the 'Resolved' date of the work item remains as-is, i.e. it is unchanged when EnateAI automatically re-resolves the work item. Check out this video to find out more, and also see the [**FAQ**](#faqs-enateai-thank-you-email-evaluation) section for further information: {% embed url="" %} ### Inputs & Outputs
## How does EnateAI 'Thank You' Email Evaluation work at runtime In Work Manager, when the AI closes a work item that has been re-opened by a thank you email, the status of the work item will be moved to resolved and a reason of 'updated by integration' will be provided to let the service agent know that the AI carried out this action.
## How to turn on EnateAI 'Thank You' Email Evaluation EnateAI requires zero configuration by Builder users and they can activate EnateAI 'Thank You' Email Evaluation via the Enate Marketplace using just one click. Activating EnateAI 'Thank You' Email Evaluation will enable it for all mailboxes.
Builder users can dis-able 'Thank You' Email Evaluation on a mailbox-by-mailbox basis.
### How do you set the confidence threshold for EnateAI Document Classification Builder users can change the confidence threshold via the integrations section of the settings page of Builder.
*** ## FAQs - EnateAI Thank you Email Evaluation Thank You Email Evaluation prevents simple thank‑you replies from creating unnecessary work for your team When a new email arrives, Enate automatically re‑opens the associated resolved work item. Thank You Email Evaluation then analyses the body of the latest two emails in the chain to determine whether the new message is a genuine thank‑you with no further intent. The AI assigns a confidence score to this assessment. If the confidence is above the configured threshold, the work item is automatically closed again so it does not clutter the queue. If the confidence is below the threshold, the work item remains open for an agent to review and decide on the next steps. **What does Thank you Email Evaluation do?** Thank you Email Evaluation identifies when a new incoming email is a simple thank‑you message. Because Enate always creates a new work item when an email arrives, Thank you Email Evaluation prevents these thank‑you emails from creating unnecessary reopened tickets by automatically closing them when appropriate. **Why is this useful?** Many customers send thank you messages after an issue has been resolved. Without Thank You Email Evaluation, every one of these messages triggers a new work item and forces agents to manually close them again. Thank you Email Evaluation automates this behaviour, keeping queues cleaner and reducing repetitive admin work. **\*\*What content does the AI analyse?\*\*** The AI reads the body of the latest email along with the body of the previous email in the chain. This helps it determine whether the new message is a pure thank‑you or contains a new request. **How does the AI decide whether an email is a genuine thankyou?** The AI checks whether the new email contains only closing language, such as gratitude or signoff. It also checks the previous email to see whether there was any outstanding request or instruction. If the new email includes new intent such as a question or a follow up action, it will not be treated as a thankyou and will remain open. **What happens when the AI confidence is above my threshold?** When the confidence score meets or exceeds your chosen threshold, Thank you Email Evaluation automatically closes the newly created work item and prevents it from appearing as reopened work in agent queues. **What happens when the confidence score is below the threshold?** If the confidence score falls below the threshold, the work item reopens and moves to the To Do state so that an agent can review the message and decide whether follow up is needed. **Can I start with a high threshold first?** Yes. Many teams begin with a 110% threshold to see which emails the AI would have closed, without allowing it to take action. This helps build trust before lowering the threshold to enable auto closure. **Is the AI keyword based?** No. The AI evaluates intention and meaning, not just keywords. For example, a message that says “Thanks” but includes a request such as “Could you also check X?” will not be treated as a thankyou email. **Is any training required?** No. Thank you Email Evaluation is ready to use immediately with no setup, tuning or training required. *** ### Third party providers Third party providers of document classification integrations can be found [here](https://docs.enate.net/enate-help/integrations/enate-integrations/auto-evaluate-thank-you-emails-thank-you-email-evaluation). --- # 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://docs.enate.net/enate-help/enateai/enateai/enateai-for-email/enateai-thank-you-email-evaluation.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.