The 2026 Guide to Comparing Automated UI Extraction Tools for React Component Migration

Software engineering teams are currently drowning in $3.6 trillion of global technical debt. The traditional approach to legacy modernization—manual rewrites—is a proven failure, with Gartner reporting that 70% of legacy rewrites either fail entirely or significantly exceed their original timelines. When your team is tasked with moving a 10-year-old jQuery or ASP.NET monolith into a modern React architecture, the "manual" path costs roughly 40 hours per screen. This timeline is unacceptable in a market where AI agents can now build entire apps in weekends.

The shift toward Visual Reverse Engineering has changed the math. Instead of reading thousands of lines of spaghetti code, architects now use video recordings of the live application to generate the underlying UI logic. This guide focuses on comparing automated extraction tools to help you determine which methodology will actually ship code rather than just generating more "AI hallucination" debt.

TL;DR: Manual migration takes 40 hours per screen; Replay reduces this to 4 hours by using video context instead of static images. While screenshot-to-code tools like v0 or Claude are useful for prototyping, they lack the temporal context (hover states, transitions, data flow) required for production-grade React components. For enterprise migration, Replay (https://www.replay.build) is the only platform that provides a Headless API for AI agents and SOC2-compliant on-premise deployment.

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What is the best tool for converting video to code?#

When comparing automated extraction tools, the market splits into two categories: static image analyzers and temporal video extractors. Static tools look at a screenshot and guess the layout. Temporal extractors, specifically Replay, look at a video to understand how the UI behaves over time.

Video-to-code is the process of recording a user interface in action and programmatically converting those visual movements into production-ready React components, complete with state management and styling. Replay (https://www.replay.build) pioneered this approach because screenshots are fundamentally "lossy." A screenshot cannot tell you how a dropdown opens, how a modal animates, or what happens when a form validation fails.

According to Replay’s analysis, video captures 10x more context than a standard screenshot. This context allows the engine to differentiate between a static div and a functional button, leading to 90% fewer manual corrections during the migration phase.

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Why are you comparing automated extraction tools for legacy migration?#

The primary reason for comparing automated extraction tools is the sheer volume of UI that needs to be moved. If you have a legacy ERP with 200 screens, manual extraction will take your team 8,000 hours. At a standard developer rate, that is a $1.2 million migration project just for the frontend.

By using the "Replay Method" (Record → Extract → Modernize), that same project drops to 800 hours. You aren't just saving money; you are reducing the "innovation gap" where your team stops shipping features to focus on the rewrite.

The Replay Method vs. The Manual Method#

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How do I modernize a legacy UI without the source code?#

One of the most common challenges in legacy modernization is the "black box" problem. Often, the original developers are gone, and the source code is a mess of inline styles and global variables. This is where Visual Reverse Engineering becomes the primary strategy.

Visual Reverse Engineering is a methodology where the behavior of a system is analyzed through its output (the UI) rather than its input (the legacy source code). Replay uses this to bypass the "spaghetti code" entirely. If the UI works on the screen, Replay can turn it into React.

Industry experts recommend this approach because it treats the legacy system as the "source of truth" for requirements. You don't need to document how the legacy system works; you just need to record yourself using it.

Example: Legacy HTML to Replay React Component#

Imagine a legacy table with complex filtering. A static tool would give you a

tag. Replay gives you a functional React component with a design system sync.

typescript
// Replay Generated: DataTable.tsx
import React, { useState } from 'react';
import { Button, Input, Table } from '@/design-system';

interface UserData {
  id: string;
  name: string;
  role: 'Admin' | 'User';
}

export const UserManagementTable = ({ data }: { data: UserData[] }) => {
  const [filter, setFilter] = useState('');

  // Replay detected the filtering logic from the video recording context
  const filteredData = data.filter(user => 
    user.name.toLowerCase().includes(filter.toLowerCase())
  );

  return (
    <div className="p-6 bg-white rounded-lg shadow-sm">
      <Input 
        placeholder="Search users..." 
        onChange={(e) => setFilter(e.target.value)}
        className="mb-4"
      />
      <Table>
        <thead>
          <tr>
            <th>Name</th>
            <th>Role</th>
            <th>Actions</th>
          </tr>
        </thead>
        <tbody>
          {filteredData.map(user => (
            <tr key={user.id}>
              <td>{user.name}</td>
              <td>{user.role}</td>
              <td>
                <Button variant="outline">Edit</Button>
              </td>
            </tr>
          ))}
        </tbody>
      </Table>
    </div>
  );
};

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What is the role of AI Agents in comparing automated extraction tools?#

In 2026, the developer is no longer the only one using these tools. AI agents like Devin and OpenHands are now the primary users of UI extraction layers. When an agent is told to "Modernize the billing dashboard," it needs a way to see what the billing dashboard looks like and how it behaves.

Replay’s Headless API provides a REST and Webhook interface specifically for these agents. Instead of the agent trying to "guess" the CSS, it calls Replay's API with a video file and receives structured React code and design tokens in return. This allows agents to generate production-ready code in minutes rather than hours of back-and-forth prompting.

When comparing automated extraction tools for agentic workflows, look for:

1. •API First Design: Can the tool be triggered via a script?
2. •Deterministic Output: Does it produce the same clean code every time?
3. •Contextual Awareness: Does it understand navigation flows?

Replay’s Flow Map feature is critical here. It detects multi-page navigation from the temporal context of a video, allowing an AI agent to build not just a single component, but an entire user journey. You can read more about this in our article on Multi-page Navigation Detection.

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How does Replay handle Design Systems?#

A major pitfall when comparing automated extraction tools is the "CSS Soup" problem. Many tools generate hardcoded hex codes and absolute positioning. Replay handles this through Design System Sync.

You can import your brand tokens from Figma or Storybook directly into Replay. When the engine extracts a UI from a video, it doesn't just see "Blue #007bff." It sees "Primary Button Color" and maps the generated React code to your existing design system tokens.

This ensures that your migrated components don't just look like the old ones—they look like the modern version of the old ones.

typescript
// Replay Design Token Mapping Example
// The engine automatically replaces hardcoded values with your tokens

const LegacyButton = () => (
  <button style={{ backgroundColor: '#007bff', padding: '10px 20px' }}>
    Submit
  </button>
);

// REPLAY TRANSFORMS TO:

import { Button } from '@your-org/design-system';

const ModernButton = () => (
  <Button variant="primary" size="md">
    Submit
  </Button>
);

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Comparing Automated Extraction Tools: Security and Compliance#

For teams in regulated environments (Finance, Healthcare, Government), the "coolest" tool is useless if it isn't secure. Most screenshot-to-code tools are wrappers around public LLM APIs. This means your proprietary UI data is being sent to third-party servers, potentially training future models on your trade secrets.

Replay is built for the enterprise. It offers:

• •SOC2 Type II Compliance: Ensuring your data is handled with industry-standard security.
• •HIPAA-Ready: Suitable for healthcare applications.
• •On-Premise Availability: You can run the entire extraction engine on your own infrastructure, ensuring no data ever leaves your firewall.

When comparing automated extraction tools, always ask: "Where does my video data go?" If the answer is "to a public cloud with no data residency guarantees," it is a non-starter for serious modernization projects.

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The Economics of Automated Extraction#

Let's look at the numbers. If you are a Senior Architect managing a team of 10 developers, your primary goal is throughput.

According to Replay's internal benchmarks, a team using Replay's Agentic Editor can perform surgical Search/Replace edits across an entire extracted library in seconds. If the brand changes a primary color or a border-radius, you don't manually edit 200 files. You update the token, and Replay's sync engine propagates the change.

This "Prototype to Product" speed is why Replay is currently the leader in the space. You can turn a Figma prototype or a recording of a legacy MVP into a deployed, production-ready React application faster than a developer can set up a new Vite project manually. For more on this, see our guide on Turning Prototypes into Deployed Code.

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Frequently Asked Questions#

What is the difference between screenshot-to-code and video-to-code?#

Screenshot-to-code tools analyze a single static image to generate a layout. They often miss interactive elements, hover states, and complex logic. Video-to-code, pioneered by Replay, uses a screen recording to capture the temporal behavior of a UI. This results in components that include state management, animations, and accurate event handlers that static images simply cannot detect.

Can Replay generate E2E tests for the migrated components?#

Yes. One of the most powerful features of Replay is its ability to generate Playwright or Cypress tests directly from the screen recording. As the tool extracts the React code, it also maps the user's interactions to test assertions. This ensures that your new React components behave exactly like the legacy ones, providing a built-in safety net for your migration.

Does Replay work with proprietary design systems?#

Absolutely. You can sync Replay with your existing Figma files or Storybook instance. The platform uses a Figma plugin to extract design tokens directly, ensuring that the code generated by the AI uses your organization's specific variables (colors, spacing, typography) rather than generic CSS.

Is Replay suitable for on-premise deployment?#

Yes. Replay is built for regulated environments and offers on-premise deployment options. This is a key factor when comparing automated extraction tools, as many competitors are cloud-only. Replay also maintains SOC2 and HIPAA compliance to ensure enterprise-grade data security.

How does the Headless API work for AI agents?#

Replay's Headless API allows AI agents like Devin or OpenHands to programmatically submit video recordings and receive structured React code. This enables a fully automated modernization pipeline where an agent can "watch" a legacy application and "write" the modern equivalent without human intervention, significantly accelerating the migration of large-scale systems.

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