Shared AI Architecture Pattern
Flutter SDK
Flutter SDK
Next.js
Building for Android and iOS is table stakes. In 2025, your users also expect a web experience. The challenge: how do you share AI logic across a Flutter mobile app and a Next.js web app without duplicating your most important code?
What to share vs. what to keep separate
The mistake most teams make is trying to share too much. Here's the practical split:
Share via API / Backend
- • AI prompt templates
- • LLM routing logic
- • Response validation
- • Business rules
- • User data & preferences
Keep Platform-Specific
- • UI components
- • Navigation
- • Platform permissions
- • Native integrations
- • Animation details
The backend-as-shared-layer pattern
The cleanest architecture in 2025 is a thin backend that handles all AI calls, and frontend clients (Flutter + Next.js) that are purely UI.
Your Node.js or Python backend exposes a clean API. The Flutter app and Next.js app both consume it. The AI logic lives in one place, gets tested in one place, and gets updated in one place.
Handling streaming across platforms
Streaming AI responses is crucial for UX. Both Flutter and Next.js handle Server-Sent Events well:
- Backend: stream the Gemini response via SSE
- Flutter: use
http.Clientwith streaming response - Next.js: use the
ReadableStreamAPI in a Route Handler
State synchronisation
If your users switch between mobile and web (they will), you need conversation history to sync. Use Firebase Firestore for real-time sync — it works natively with Flutter and via the JavaScript SDK in Next.js.
Authentication
Firebase Authentication handles both Flutter and Next.js out of the box, with the same user identity across platforms. Use it.
The teams shipping the best multiplatform AI apps aren't the ones who wrote the cleverest platform-specific code. They're the ones who identified the shared layer early and resisted the temptation to duplicate it.