u/Ill-Connection-5578

I recently worked on building a real-time AI avatar app in Flutter, and the biggest challenge was not the UI layer itself, but coordinating the entire real-time interaction pipeline in a stable way on mobile. >>Github Project

The system involved:

• speech recognition
• LLM response generation
• text-to-speech
• digital human rendering
• RTC streaming
• Flutter video playback

Individually, each component is manageable. The complexity comes from making them work together with low enough latency for natural conversation.

Initially, I considered combining separate ASR, LLM, TTS, and WebRTC services manually. However, once the project moved into real-time interaction, several engineering problems appeared quickly:

• synchronization between speech and avatar rendering
• token authentication and RTC session management
• Android rendering stability
• concurrent instance cleanup
• audio-only publishing workflows
• stream lifecycle management

Building the interaction pipeline itself turned out to be much more challenging than building the Flutter UI.