> For the complete documentation index, see [llms.txt](https://docs.scaleconnect.com.au/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.scaleconnect.com.au/scaleconnect-docs/messaging/client-chatbot.md). # Client Chatbot The Client Chatbot is the direct messaging channel between you and your clients. Clients message you through ScaleApp on their phone; you see and reply from the client panel in ScaleConnect. Every conversation is tied to the client's profile, so the full thread sits alongside their portfolio data, notes, and AI history. ScaleAI works behind the scenes here too — generating suggested responses based on the client's current position, recent activity, and conversation context so you can reply faster without losing the personal touch. *** ## How It Works How messages flow between ScaleApp (client side) and ScaleConnect (broker side), where conversations live in the client panel, and how the chatbot integrates with the rest of the client's profile. *** ## Suggested Responses How ScaleAI generates contextual reply suggestions based on the client's portfolio data, recent questions, and conversation history — and how to use, edit, or dismiss them. *** ## Notifications and Availability How you're notified of new client messages, managing response times, and how the chatbot handles messages when you're unavailable. *** ## Relationship to the AI Assistant How the chatbot and the AI Assistant complement each other — the chatbot is for direct client communication, the AI Assistant is your analytical workspace. Suggested responses draw from the same intelligence layer. *** {% hint style="info" %} The Client Chatbot keeps every client conversation in one place — right next to their portfolio, notes, and AI history — so you never lose context between what you're discussing and what you know. {% endhint %} --- # 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.scaleconnect.com.au/scaleconnect-docs/messaging/client-chatbot.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.