Conversational AI is becoming a practical way to enhance mobile apps as voice-based interaction continues to grow. Flutter makes this especially appealing by allowing developers to build cross-platform voice experiences using a single Dart codebase.
Traditionally, building a real-time voice AI system required stitching together multiple components such as audio streaming, speech recognition, language models, and text-to-speech engines. This often led to complex architectures and long development cycles.
With ZEGOCLOUD’s Conversational AI solution, these capabilities are combined into a unified real-time workflow. Flutter apps can stream audio, receive AI responses, and play synthesized speech with minimal integration effort.
In this guide, we’ll build a conversational AI app in Flutter that listens to the user, processes speech through AI, speaks back, and displays real-time subtitles.
Conversational AI Architecture Overview
A typical real-time conversational AI setup consists of three parts:
| Component | Responsibility |
|---|---|
| Backend Server | Keeps API keys secure and controls the AI agent lifecycle |
| Flutter App | Captures audio, plays responses, and renders the UI |
| ZEGOCLOUD | Handles ASR, LLM processing, and TTS in real time |
All sensitive credentials remain on the server, while the Flutter app focuses on audio handling and interaction logic.
What ZEGOCLOUD Provides for Flutter
ZEGOCLOUD is a real-time communication platform offering SDKs and APIs for voice, video, and interactive AI experiences.
For conversational AI, it provides:
- Real-time audio streaming
- Automatic speech recognition
- LLM-based response generation
- Natural text-to-speech output
Flutter developers benefit from a single Dart-based integration without managing separate speech or AI services. Optional UIKits(https://www.zegocloud.com/uikits) are also available for faster UI setup.
Prerequisites
Before starting, make sure you have:
- Flutter 3.0 or above
- A ZEGOCLOUD account
- Basic Dart knowledge
- A simple backend service (Next.js works well)
Step 1: Backend Setup
The backend is responsible for token generation and AI agent control.
Environment Variables
Create a .env.local file:
NEXT_PUBLIC_ZEGO_APP_ID=your_app_id
ZEGO_SERVER_SECRET=your_server_secret
SYSTEM_PROMPT="You are a friendly AI assistant."
LLM_URL=https://your-llm-provider.com/api/chat/completions
LLM_API_KEY=your_llm_api_key
The backend keeps all sensitive credentials secure and issues short-lived tokens to the client.
Step 2: Flutter Client Setup
Create Project
flutter create aiagent_demo
Dependencies
Add the following to pubspec.yaml:
dependencies:
flutter:
sdk: flutter
zego_express_engine: ^3.22.0
http: ^1.2.0
permission_handler: ^11.3.0
Platform Permissions
Enable microphone access on both Android and iOS to support voice interaction.
Step 3: Real-Time Conversation Flow
The conversational loop follows these steps:
- 1. Request a token from the backend
- 2. Join a real-time room
- 3. Publish microphone audio
- 4. Start the AI agent
- 5. Play the AI audio stream
- 6. Display real-time subtitles
- 7. End the session and clean up
ZEGOCLOUD handles audio streaming, AI reasoning, and speech synthesis during the session.
Subtitles and Live Feedback
Real-time subtitles improve usability by showing both user speech and AI responses as text. ZEGOCLOUD provides a ready-made subtitles component that supports:
- ASR transcripts
- Incremental AI responses
- Message ordering
This removes the need to build a custom subtitle pipeline.
Run the App
flutter run -d ios
flutter run -d android
Final Thoughts
This tutorial demonstrated how to build a real-time conversational AI app in Flutter using voice input and AI-generated responses.
By combining Flutter’s cross-platform capabilities with ZEGOCLOUD’s real-time AI infrastructure, developers can focus on interaction design instead of low-level audio handling or AI pipeline management.
This approach works well for AI assistants, education apps, customer support tools, and other voice-driven experiences.
If you’d like to explore more implementation details and advanced use cases, you can read the full blog post here:
https://www.zegocloud.com/blog/flutter-conversational-ai
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