How to build a chatbot using conversational video AI in React

Jack Virag

July 1, 2025

Table of Contents

Conversational AI is moving at lightning speed.

Not so long ago, chatbots were all about text—helpful, but often robotic and forgettable. Now, we’re entering a new era: video-powered chatbots that make digital interactions more engaging, personal, and even a little magical.

For developers and businesses, this means building experiences that genuinely connect with users, delivering conversations that feel natural and memorable.

If you’re curious about how to build a video AI chatbot in React, you’re in the right place. In this guide, we’ll walk through the core concepts, technical steps, and practical tips to help you get started with the latest in real-time, multimodal conversational technology.

Understanding video AI chatbots

Before we get into the code, let’s set the stage. Video AI chatbots aren’t just a flashy upgrade—they represent a real shift in how people and businesses connect online.

What is a video AI chatbot?

A video AI chatbot is a digital agent that interacts with users through lifelike video, powered by artificial intelligence. Instead of typing back and forth, users experience a face-to-face conversation with a digital avatar, or replica. These replicas—like those created with Tavus Conversational Video Interface (CVI)—can see, hear, and respond in real time.

What sets modern video chatbots apart is their multimodal design. This means they understand not only speech, but also facial expressions and body language. And with ultra-low latency, these avatars can respond almost instantly, making every interaction feel fluid and authentic.

Benefits of video chatbots over traditional chatbots

Switching from a text-based chatbot to a video AI chatbot unlocks several important advantages:

Real human presence: Users feel like they’re talking to a person, not just a faceless bot.
Enhanced communication: Video lets you convey emotion, tone, and nuance—things that get lost in text.
Higher engagement: People are more likely to interact and remember experiences that feel personal and authentic.
Lower friction: You don’t need to build or maintain complicated video systems. Tavus CVI handles essentials like WebRTC and speech recognition for you, right out of the box.

To bring this to life, consider the story of a customer support team that switched to a video AI chatbot powered by Tavus. Almost overnight, they saw a spike in positive feedback. Customers commented on how much more helpful and “human” the support felt, and support sessions wrapped up faster than ever.

Core components of a conversational video AI chatbot

Building a video AI chatbot is more than just hooking up a webcam. It’s about orchestrating a set of sophisticated systems to deliver smooth, natural conversations.

Video content creation and management

Creating great video assets is where it all starts. Tavus makes this easy with their Replicas—these are digital avatars you can use out of the box or train yourself using just a few minutes of your own video and voice.

When planning your chatbot, it’s smart to script responses for common user journeys. Organize and manage your video assets right in the Tavus platform or via API, so integration into your React app is seamless.

Keep in mind, video generation can take a few minutes depending on script length. Thanks to non-deterministic AI models, each video response is unique—even if the script stays the same—bringing a natural touch to every conversation.

AI and natural language processing integration

At the heart of every conversational video AI chatbot is a smart AI layer. Large language models (LLMs) interpret user input, whether it comes in as speech or text. Tavus CVI integrates with optimized LLMs but gives you the freedom to connect your own models or use real-time APIs like OpenAI.

Conversation turns are managed by systems like Sparrow (handling who speaks when) and Raven (managing perception and context). Together, they keep the conversation flowing naturally, so users never feel like they’re talking to a script.

User interaction and conversational flow

The user experience is everything. With Tavus CVI, users interact through a video interface and get prompt responses. Real-time speech recognition ensures the chatbot understands spoken input, while natural turn-taking makes conversations feel like, well, real conversations.

You can also customize how your chatbot handles interruptions, fallback responses, and the overall look and feel of the UI. This flexibility lets you shape the experience to fit your audience perfectly.

Step-by-step guide: Building a video AI chatbot in React

Let’s get hands-on. Here’s how you can build and launch your own video AI chatbot using React and Tavus CVI.

Setting up your React environment

First, set up your React project. If you haven’t already, initialize your app with a tool like Create React App or Vite. You’ll also want to install key dependencies—@daily-co/daily-js is a great choice for handling video conferencing needs.

Next, head over to the Tavus developer portal to grab your API key. This will unlock access to the Conversational Video Interface and all the features you’ll need.

Integrating video assets and UI components

Embedding your video chatbot into your app is straightforward. Use the Daily iframe to host the conversation UI, then render the video chatbot inside your React component.

Here’s a simplified example using useEffect and refs to load the Daily video iframe, join the conversation, and handle messages:‍

import React, { useEffect, useRef } from 'react';

function VideoChatbot() {
  const iframeRef = useRef();

  useEffect(() => {
    const dailyIframe = document.createElement('iframe');
    dailyIframe.src = 'YOUR_TAVUS_CONVERSATION_URL';
    dailyIframe.width = '100%';
    dailyIframe.height = '600';
    iframeRef.current.appendChild(dailyIframe);

    // Add event listeners if needed
    return () => {
      iframeRef.current.removeChild(dailyIframe);
    };
  }, []);

  return <div ref={iframeRef} />;
}

‍The first time you see your own digital avatar responding in real time, it’s an uncanny—and honestly, exciting—moment. It brings your project to life in a way that static chatbots never could.

Connecting to AI backend for conversational logic

To make the chatbot truly conversational, connect your UI to the Tavus backend using a conversation URL. Listen for app-message events to handle real-time interactions.

When a user sends a message, the system routes the query to the LLM, matches it to the right video response, and streams the result back—usually in under a second. This lightning-fast turnaround is what makes the experience feel genuinely interactive.

If you ever run into issues with video generation, double-check that your script isn’t too long and your replica is set up correctly. These are common hiccups when you’re starting out.

Enhancing your chatbot: Logic, personalization, and testing

A great chatbot isn’t just about functionality—it’s about delivering a personal, responsive, and always-improving experience.

Implementing conditional logic and fallbacks

Real conversations are unpredictable. To keep yours on track, use conditional logic to match user queries with the right video responses. Set up fallback answers for unexpected questions, so the conversation never stalls.

With Tavus’s perception layers, you can make your chatbot more context-aware. This helps the agent pick up on subtle cues and steer the conversation in the right direction.

Personalizing the experience with video avatars and custom scripts

Personalization is where video chatbots really shine. With the Tavus persona system, you can create custom avatars for specific roles—think digital sales agents, coaches, or tutors.

Customize scripts and video flows for different user segments, and use multi-step flows to guide users through complex tasks or decisions. For example, a startup recently used a personalized onboarding agent to walk new customers through setup. The friendly, face-to-face experience boosted user activation and made the onboarding process memorable.

Testing, analyzing, and optimizing performance

Building your chatbot is just the beginning. Test it in a variety of scenarios to make sure it handles real-world conversations smoothly.

Use analytics to track engagement, spot areas for improvement, and measure response accuracy and session completion rates. Refine your scripts and logic based on real feedback—this ongoing iteration is the key to creating an experience people love.

Deployment, embedding, and real-world applications

Once your video AI chatbot is polished, it’s time to share it with the world.

Deploying the React video chatbot

Prepare your React app for production by building and optimizing your project. Deploy to your preferred hosting platform—whether that’s Vercel, Netlify, AWS, or another provider.

Remember to manage your API keys securely and double-check your environment configuration before going live.

Embedding and sharing your chatbot

You can embed your chatbot UI in any website or web app with just a few steps. Drop in the iframe or React component where you want it to appear.

Share conversation URLs so users can jump right in. For best results, think carefully about widget placement and onboarding instructions—making it easy for users to find and start a conversation boosts engagement from day one.

Next steps: Start building your video AI chatbot

Video AI chatbots are opening up new ways for businesses and creators to connect with their audiences—naturally, at scale, and with a human touch.

Jump into your own project by experimenting with Tavus CVI and React. Train a custom replica, try out advanced scripting, or integrate your chatbot with your backend logic. Each step you take will help you create digital experiences your users will remember.