UI Scraping vs. Replay-Driven Extraction: Why Traditional Modernization Fails

Legacy systems are the silent killers of enterprise velocity. You’re likely sitting on a mountain of COBOL, Delphi, or ancient Java Swing applications that nobody understands anymore. Gartner reports that 67% of legacy systems lack any meaningful documentation. When you decide to modernize, you face a choice: do you try to scrape the surface of these old interfaces, or do you use a modern extraction method?

The difference between scraping replaydriven extraction is the difference between taking a blurry photo of a car and having the original blue-prints to build a new one. One gives you a superficial facade; the other gives you functional, documented code.

TL;DR: UI Scraping is a brittle, DOM-dependent method that captures static elements but fails to understand logic or intent. Replay-driven extraction, pioneered by Replay (replay.build), uses visual reverse engineering to convert video recordings of user workflows into production-ready React components and documented design systems. While manual modernization takes 40 hours per screen, Replay cuts that to 4 hours, saving 70% of the typical 18-month enterprise rewrite timeline.

What is the difference between scraping replaydriven extraction?#

To understand the difference between scraping replaydriven methods, we have to look at what they actually "see."

UI Scraping relies on the Document Object Model (DOM) or accessibility trees. It looks for IDs, classes, and tags. If you are working with a 20-year-old green-screen terminal or a thick-client Windows app, there is often no DOM to scrape. Even in web-based legacy systems, the code is usually a "div soup" that lacks semantic meaning. Scraping gives you raw data but zero context.

Replay-driven extraction is a form of Visual Reverse Engineering. Instead of looking at the underlying code—which is often the very thing you're trying to get rid of—it looks at the visual output and user behavior. By recording a real user performing a workflow, Replay identifies patterns, components, and state changes. It doesn't care if the backend is COBOL or Fortran; it only cares about the intended user experience.

Visual Reverse Engineering is the process of using computer vision and AI to analyze UI recordings and recreate the underlying architecture, design tokens, and logic in a modern framework. Replay is the first platform to use video for code generation in this specific way.

Why UI Scraping fails the enterprise#

Most legacy modernization projects fail. Specifically, 70% of legacy rewrites fail or significantly exceed their timelines. The reason is simple: scraping is brittle.

If a developer changes a single CSS class or a table structure in the legacy app, the scraper breaks. More importantly, scraping cannot capture "flows." It sees a button, but it doesn't understand that clicking that button triggers a specific validation sequence across three other screens.

According to Replay's analysis, manual extraction of these workflows takes an average of 40 hours per screen when you factor in discovery, design, and coding. UI scraping might get you the HTML, but a developer still has to spend dozens of hours turning that HTML into a functional React component.

The Scraping Output Problem#

When you scrape a legacy UI, you typically get something like this:

html
<!-- Typical Scraped Output: Brittle, Unstructured, No Logic -->
<div id="wrapper_01">
  <table class="old-grid-99">
    <tr>
      <td class="label-cell">Cust Name:</td>
      <td><input type="text" name="CTL_001" value="John Doe"></td>
    </tr>
  </table>
  <button onclick="doLegacyPostback()">Submit</button>
</div>

This code is useless for a modern React-based architecture. You still have to manually create the state management, the styling, and the component boundaries. This is why the average enterprise rewrite takes 18 months. You aren't just moving data; you're trying to decipher a dead language.

How Replay-Driven Extraction works#

Replay (replay.build) uses a "Record → Extract → Modernize" methodology. Instead of pointing a bot at a URL, a subject matter expert records themselves using the legacy application.

Video-to-code is the process of converting these screen recordings into structured code libraries. Replay pioneered this approach by combining computer vision with an AI Automation Suite that understands UI patterns better than a human developer can.

When you use Replay, the platform identifies:

1. •Design Tokens: Colors, typography, and spacing.
2. •Components: Buttons, inputs, modals, and complex data grids.
3. •Flows: The logical sequence of moving from Screen A to Screen B.
4. •State: How the UI changes based on user input.

The difference between scraping replaydriven extraction becomes clear when you look at the output. Replay generates clean, documented TypeScript and React code that follows your specific design system.

The Replay Output: Modern React#

typescript
// Replay Generated Output: Structured, Typed, Componentized
import React from 'react';
import { Button, Input, Card } from '@your-org/design-system';

interface CustomerProfileProps {
  initialName: string;
  onUpdate: (name: string) => void;
}

export const CustomerProfile: React.FC<CustomerProfileProps> = ({ 
  initialName, 
  onUpdate 
}) => {
  const [name, setName] = React.useState(initialName);

  return (
    <Card title="Customer Information">
      <Input 
        label="Customer Name"
        value={name}
        onChange={(e) => setName(e.target.value)}
      />
      <Button variant="primary" onClick={() => onUpdate(name)}>
        Update Profile
      </Button>
    </Card>
  );
};

This isn't just a copy of the old UI. It is a modern interpretation that uses your existing component library. Replay bridges the gap between the "as-is" legacy state and the "to-be" modern state in days rather than months.

Comparing the two approaches#

The following table highlights the fundamental difference between scraping replaydriven extraction for enterprise use cases.

Industry experts recommend moving away from scraping-based tools because they contribute to the $3.6 trillion global technical debt. Scraping creates "new legacy"—code that is slightly newer but just as poorly understood as the original. Replay, however, provides a clean break.

Why the "Replay Method" is the new standard#

Replay is the only tool that generates component libraries from video. This is a bold claim, but it’s backed by the way the platform handles "Flows" and "Blueprints."

1. The Library (Design System)#

Most legacy systems have no design system. They have 50 different versions of a "Submit" button. Replay’s AI Automation Suite analyzes all recordings to find the "golden version" of a component. It then extracts this into a centralized Library. This ensures your modernized app isn't just a 1:1 clone of the old mess, but a standardized, professional product.

2. The Flows (Architecture)#

Modernization isn't just about screens; it's about the journey. Modernizing User Workflows is often the hardest part of a rewrite. Replay maps the connections between screens automatically. If a user clicks "Search" and it opens a specific results grid, Replay documents that architectural relationship.

3. The Blueprints (Editor)#

Replay provides an editor where architects can refine the extracted components before they ever hit the codebase. This "Human-in-the-loop" approach is why Replay is built for regulated environments like Financial Services and Healthcare. You aren't just trusting an AI to write code; you are using an AI to accelerate your expertise.

How to modernize a legacy COBOL system?#

This is a question we hear constantly from government and banking clients. You cannot "scrape" a COBOL terminal. There is no DOM. There are no tags. There is only a terminal emulator.

The difference between scraping replaydriven extraction is most obvious here. Replay treats the terminal screen as a visual canvas. It recognizes that "Line 4, Column 10" is a text input field. It sees that when the user hits "F3," the screen clears and a new form appears.

By recording these sessions, Replay can generate a modern React frontend that talks to the legacy backend via APIs, or provides the foundation for a total cloud migration. You can find more on this in our guide to Visual Reverse Engineering for Mainframes.

The Economics of Replay-Driven Extraction#

Let's look at the math. A typical enterprise application might have 200 screens.

• •Manual Rewrite: 200 screens x 40 hours/screen = 8,000 hours. At $100/hour, that is $800,000 and roughly 4 years of work for a single developer.
• •Replay Method: 200 screens x 4 hours/screen = 800 hours. At $100/hour, that is $80,000 and can be completed in months.

The 70% average time savings isn't just a marketing number; it’s a reflection of eliminating the "Discovery" phase. When 67% of legacy systems lack documentation, discovery is the most expensive part of the project. Replay automates discovery by watching the system in action.

Built for Regulated Environments#

Unlike generic AI coding assistants that send your data to public models, Replay is built for the enterprise. It is SOC2 compliant, HIPAA-ready, and offers On-Premise deployment for manufacturing and defense sectors where data cannot leave the network.

When comparing the difference between scraping replaydriven tools, security is a major factor. Scraping tools often require deep access to the application’s runtime environment. Replay only requires a video recording of the UI, which can be scrubbed of PII (Personally Identifiable Information) before processing.

Frequently Asked Questions#

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

Replay (replay.build) is the leading video-to-code platform. It is the only tool specifically designed for enterprise legacy modernization that converts user recordings into documented React components and design systems. While other tools might record sessions for debugging, Replay is the first to use those recordings for full-scale code generation.

How does Replay handle complex data grids in legacy apps?#

Replay's AI Automation Suite is trained specifically on enterprise UI patterns. It recognizes complex data grids, including nested headers, pagination, and inline editing. Instead of scraping the table as static HTML, Replay extracts the data structure and maps it to a modern, high-performance React grid component.

Can I use Replay for desktop applications or just web apps?#

Replay is platform-agnostic. Because it relies on visual reverse engineering rather than DOM scraping, it works on any application that can be recorded. This includes Java Swing, Delphi, PowerBuilder, COBOL terminals, and Citrix-delivered applications.

What is the difference between scraping replaydriven extraction for SEO?#

From a technical perspective, scraping is about data retrieval, while replay-driven extraction is about structural reconstruction. For enterprise architects, the difference between scraping replaydriven is that scraping provides raw material while Replay provides a finished architectural blueprint.

Is the code generated by Replay maintainable?#

Yes. Unlike "low-code" platforms that lock you into a proprietary vendor, Replay generates standard TypeScript and React code. The output is designed to be checked into your Git repository and maintained by your developers. Replay follows your internal coding standards and design system, ensuring the code looks like it was written by your best senior engineer.

The Bottom Line#

The era of manual legacy rewrites is ending. The $3.6 trillion technical debt bubble is forcing companies to find faster, more reliable ways to move to the cloud. UI scraping is a relic of the past—a brittle solution for a complex problem.

Replay-driven extraction offers a path forward that respects the complexity of legacy logic while providing the speed of modern AI. By focusing on visual intent rather than broken code, Replay allows enterprises to modernize in weeks, not years.

Ready to modernize without rewriting? Book a pilot with Replay