> For the complete documentation index, see [llms.txt](https://build-ai.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://build-ai.gitbook.io/docs/roadmap-ai-agents-q3-and-q4.md). # Roadmap: AI Agents - Q3 & Q4 #### **Meta Integration & Engagement Tools** * Integrate BuildAI chatbot with Messenger and WhatsApp via Meta API * Enable bi-directional messaging, webhook handling, and basic analytics * **Deliverable:** Live Meta channels ready for user interactions * Build backend service to schedule and publish posts on Facebook & Instagram * Develop admin UI for composing, scheduling, and monitoring post performance * **Deliverable:** Automated posting pipeline and UI component *** #### **Product Display & Platform Connectors** * Create endpoint for fetching product metadata (image, URL, details) * Develop interactive product cards in chat with actionable buttons * Build Shopify & WordPress connectors to sync products and support “Fetch → View → Cart” flow * **Deliverable:** Product card feature + Shopify & WordPress sync *** #### **Memory Services & Model Flexibility** * Design persistent storage for leads (Name, Phone, Address) * Expose APIs to recall and update lead data in active chats * Implement multi-model support: runtime model switching per task/channel * **Deliverable:** Lead memory API + model abstraction layer *** #### **Credits Management & Order Adapters** * Build a credits ledger to track API/resource usage per user * Create a dashboard to monitor and recharge credits * Design an adapter system to convert chat orders into backend-compatible formats * Implement a Restaurant adapter with API connections and callbacks * **Deliverable:** Full credits module + Restaurant order adapter --- # 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://build-ai.gitbook.io/docs/roadmap-ai-agents-q3-and-q4.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.