> For the complete documentation index, see [llms.txt](https://help.qwary.com/product-guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.qwary.com/product-guide/insights/text-ai.md). # Text AI With the help of AI, brands can save time and effort by automatically analyzing feedback from customers and employees. Text AI can help in analyzing customer feedback by extracting keywords and phrases which are important to the customer. It can also help in understanding the sentiment of the comments. For example, if a customer says, “I love this product,” then this is an indication that they are happy with their purchase. But if they say, “I don’t like this product,” then it means that they are not satisfied with their purchase. Similarly, for employee feedback analysis, text AI can extract keywords and phrases which are important to the employee. It will also understand the sentiment of comments made by employees such as “I love my job here” or “I want to quit my job here.” [Topics](/product-guide/insights/text-ai/topics.md) The topic will automatically tag your responses. It will let you create themes in feedback and generate valuable insights around volume and sentimental AI Trends on individual vs. overall topics. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## 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, and the optional `goal` query parameter: ``` GET https://help.qwary.com/product-guide/insights/text-ai.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.