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Stephen568hub
Stephen568hub

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How to Build a Conversational AI using Flutter

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
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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
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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
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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
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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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