# EnateAI Sentiment Analysis ## Overview Our sentiment analysis pattern, available in [Marketplace](https://docs.enate.net/enate-help/builder/builder-2021.1/integrations-marketplace) in Builder enables the analysis of the content of incoming emails and determine if, for example, they are positive or negative. This assessment can be passed back into Enate Work Manager so that Agents can tell at a glance what the tone of the mail is as headline information as they start to deal with it. Check out this video to find out more, and also see the [**FAQ**](#faqs-enateai-sentiment-analysis) section for further information: {% embed url="" %} ### Inputs & Outputs

## How does EnateAI Sentiment Analysis work at runtime When EnateAI Sentiment Analysis is active it will read incoming emails and highlight their sentiment using a traffic light system.

If you hover over a sentiment marker on an email the confidence score of the AI will be displayed.

## How to turn on EnateAI Sentiment Analysis EnateAI requires zero configuration by Builder users and they can activate EnateAI Sentiment Analysis via the Enate Marketplace using just one click. Activating EnateAI Sentiment Analysis will enable it for all mailboxes.

Builder users can dis-able Sentiment Analysis on a mailbox-by-mailbox basis.

### Known Issue - Out of Office Mails Please note that there is a known issue with Microsoft 365 Graph API for Outlook, which affects its ability to identify out of office emails, which are normally ignored for Sentiment Analysis. {% file src="/files/2nZEqe8qovGKxHpxgjst" %} *** ## FAQs - EnateAI Sentiment Analysis Sentiment Analysis uses AI to analyze the body of each incoming email and classify it as positive, neutral, or negative, along with a confidence score. This helps teams quickly identify frustrated customers, prioritize sensitive cases, and respond with the right level of urgency and care, without the need for manual effort. **What does Sentiment Analysis do?** Sentiment Analysis uses AI to read the **body** of an email and determine whether the overall sentiment is **positive**, **neutral**, or **negative**, along with how confident the AI is in that judgement. This gives agents quick insight into customer tone and helps your team to prioritize appropriately. **What parts of the email are analyzed?** The AI analyses only the **body** of the email. It does not use: * Subject lines * Footers or signatures * Attachments * Images or files **How does the AI determine sentiment?** The model evaluates the overall meaning and tone of the message — not just keywords. * Analyses only the latest message (ignores threads, signatures, disclaimers) * Defaults to **Neutral** unless clear emotion is present * **Positive** = explicit praise, satisfaction, or strong gratitude * **Negative** = clear frustration, criticism, or dissatisfaction * Politeness, urgency, and routine business language are Neutral unless paired with emotion **What AI model does Sentiment Analysis use?** Sentiment Analysis is powered by GPT‑4.0 mini, selected because it proved to be: * The most accurate in internal testing * The most cost-effective model to run at scale. **Is this a keyword matching system?** No - Sentiment Analysis is **not** keyword based. It interprets the full meaning and tone of the message instead of reacting to individual words. **Does Sentiment Analysis learn from our emails or user corrections?** No. There is no feedback loop and no model retraining on client data. **How accurate is Sentiment Analysis in a real workload?** We have clients using Sentiment Analysis on upwards of 15,000–20,000 emails per day, achieving 96% accuracy. **Are there any limits on email volume?** No. Sentiment Analysis can analyze emails at any scale, making it suitable for high volume operations. **How does Sentiment Analysis help agents day-to-day, and where does it add the most value?** Sentiment Analysis can be useful on a single email basis, helping agents quickly understand tone and respond appropriately. However, the *real* value emerges when you analyze sentiment trends over time. Sentiment Analysis powers a dedicated report that helps you identify patterns, hot spots and opportunities for service improvement across your operation. This includes: * Sentiment over time — track whether overall customer tone is improving or declining * Sentiment comparison by context — compare sentiment across customers, services and processes * Agents receiving the most positive or negative emails * Email sentiment by ticket categories * Top positive and negative senders * Email sentiment by the length of time a work item is open * Email sentiment by number of work items with defects This level of insight helps teams spot emerging issues early, validate process improvements, and understand the customer experience at scale — not just email by email. *** ### Third party providers Third party providers of document classification integrations can be found [here](https://docs.enate.net/enate-help/integrations/enate-integrations/analyse-sentiment-in-emails-sentiment-analysis). --- # 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/sentiment-analysis.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.