> For the complete documentation index, see [llms.txt](https://gitbook.com/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gitbook.com/docs/ai-and-search/connections/pylon.md). # Pylon ## In GitBook Assistant Conversations from Pylon can be passed as context to [GitBook Assistant](/docs/ai-and-search/gitbook-ai-assistant.md). ## In change requests GitBook Agent can [identify content gaps](/docs/gitbook-agent/automatic-docs-improvements.md) from resolved support conversations in Pylon. ## What we store * GitBook only indexes resolved conversations in Pylon that have at least one reply from a human or AI support agent. We do not index open or unresolved conversations, and we do not index spam conversations. * GitBook only stores the conversation. We do not store metadata or user information. * GitBook redacts sensitive information in the conversation before storage. We do not store sensitive information in the conversation itself. ## How to connect * Connecting to Pylon requires credentials with read access to conversations in Pylon. --- # 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://gitbook.com/docs/ai-and-search/connections/pylon.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.