Architecture Design for MeetingCompagnion SaaS

We are facing a challenge to design an architecture where every dashboard component is a self‐contained module that “talks” to a shared backend and central state. In other words, we want to break the app into discrete, focused components (MyCalendar, My History, Members, AI Companion selection, various settings, etc.) and then wire them together via a common API and a global state/context.

Suggested Approach

Modular UI Components & Routing

• Build each section as a dedicated React component:
  For example, your MyCalendar component can integrate a calendar library (or a custom calendar view) that fetches both upcoming and past meeting data, while your My History component retrieves previous meetings along with their chat logs and AI-generated summaries.
• Use React Router:
  As you already do in your App.jsx, React Router allows users to switch seamlessly between these sections. Your sidebar (see your AppSidebar component) serves as the navigation hub that links to each module.

Note: MeetingCompagnionSaaS

Centralized State Management & API Layer

• Introduce a "MeetingContext" (or use Redux):
  This will hold the current user’s meeting data, notifications, and even the current AI companion selection. A meeting scheduled in the MyCalendar module can automatically trigger a notification or update the My History view when it’s complete.

• Create a set of RESTful endpoints on your Node.js/Express backend:
  Cover the core operations:

  • Creating, updating, and deleting meetings
  • Fetching upcoming meetings (for calendar display)
  • Retrieving historical data (chat history, summaries)
  • Recording AI companion selections for live meetings

  By designing your API in a modular way, each UI component can simply call the appropriate endpoint to fetch or update its data.

Note: MeetingCompagnionSaaS

Real-Time & Notification Logic

• Integrate real-time notifications for the MyCalendar section:
  When a meeting’s start time approaches, alert the user via websockets (e.g., using Socket.io) or a server-side scheduler that sends push notifications.
• Keep the shared state updated:
  Ensure that all components (such as a notification badge in the header or updates in the calendar) remain in sync with the latest notifications.

Meeting & Companion Flow

• Prompt for AI companion selection when starting a new meeting:
  Implement this in your LiveCompanion module. The selection should be stored in local state (or localStorage for persistence) and in your global context so that the LiveMeeting component can use it for real-time transcription and summary generation.
• Design the Live Meeting interface:
  Before connecting, validate the companion selection and then launch the live session using your transcription and summarization APIs (e.g., via your Flask backend with Whisper and GPT-based summarization).

Note: MeetingCompagnionSaaS

Data Models & Persistence

• Define clear data models for meetings:
  Include fields like meeting ID, title, scheduled time, participants, selected companion, chat history, and summary.

• Utilize appropriate databases:

  • MongoDB for unstructured meeting notes and companion data
  • PostgreSQL for relational data (e.g., agendas and participant info)

  This separation allows the MyCalendar and My History modules to simply query the data they need, while the Live Meeting module can update meeting records in real time.

Inter-Component Communication

• Share data via global state (Context or Redux):
  For instance, when a user schedules a meeting in MyCalendar, the global state updates and the MeetingsHistory component can automatically reflect that new data.
• Synchronize AI Companion selection:
  The selection flows through the state so that both the selection screen and the subsequent live meeting interface remain in sync.

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In summary, decouple each UI component while connecting them through a central data store and robust backend APIs. This modular, event-driven design lets you add new features (like Teams, Billing, or Limits) in the future without re-architecting the entire system.

By planning your data flow carefully—defining clear models for meetings and user settings, establishing RESTful endpoints for every operation, and using a shared global state to synchronize data—you create a scalable, maintainable architecture for your MeetingCompagnion SaaS.

This approach is supported by the design and integration ideas outlined in your project documents, which emphasize modular UI design, real-time insights, and flexible integration with external tools Meeting-Companion, Meeting-Companion.