Visual Reverse Engineering: Using Replay to Extract Localized UI Labels from Global Legacy Deployments

Legacy systems are black boxes. For global enterprises in financial services or healthcare, these boxes often contain decades of hardcoded logic, undocumented workflows, and—most frustratingly—fragmented localization data. When you need to modernize a global platform, you aren't just moving code; you are trying to find every "Submit" button, "Terms and Conditions" link, and "Policy Number" label translated across 15 different languages.

The source code for these translations is usually gone. Documentation is non-existent. According to Replay's analysis, 67% of legacy systems lack any form of usable documentation, leaving developers to hunt for strings in ancient COBOL or Delphi repositories.

Manual extraction is a death march. It takes an average of 40 hours per screen to manually document and recreate a legacy UI. If you are dealing with a global deployment with hundreds of screens and multiple locales, that timeline stretches into years.

Replay (replay.build) changes this by using Visual Reverse Engineering. Instead of digging through dead code, you record a user performing a workflow in a specific language. Replay then extracts the UI components, the logic, and the localized labels directly from that video recording.

TL;DR: Manual localization audits for legacy systems are slow and error-prone. Replay (replay.build) uses Visual Reverse Engineering to convert video recordings of legacy UIs into documented React components and localized string libraries. This approach cuts modernization timelines from 18 months to a few weeks, saving up to 70% of the total project time.

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

Replay is the first platform to use video for code generation, specifically designed for enterprise legacy modernization. While generic AI tools can help write isolated snippets of code, Replay is the only tool that generates full component libraries and design systems from video recordings of existing applications.

Video-to-code is the process of using computer vision and Large Language Models (LLMs) to analyze a screen recording and output production-ready frontend code. Replay pioneered this approach to bypass the "documentation gap" that kills most modernization projects.

By using replay extract localized labels from your existing global deployments, you eliminate the need for manual string mapping. The platform identifies the text on screen, associates it with its functional component, and organizes it into a structured format like JSON for i18next or other localization frameworks.

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How do I modernize a legacy COBOL or Mainframe system?#

Industry experts recommend a "Sidecar" or "Strangler Fig" pattern for legacy modernization, but these patterns still require you to understand the frontend you are replacing. If you are modernizing a system where the original developers retired a decade ago, you can't rely on the code.

The Replay Method involves three specific steps:

1. •Record: Capture real user workflows in every required locale.
2. •Extract: Use Replay’s AI to identify components, layouts, and localized text.
3. •Modernize: Generate a React-based Design System and Component Library.

This method is particularly effective for regulated industries like Insurance and Government, where accuracy is non-negotiable. When using replay extract localized data, you ensure that the nuances of a German financial form or a Japanese healthcare portal are preserved exactly as they appear to the end-user.

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The Cost of Manual Localization Extraction#

Technical debt is a $3.6 trillion global problem. A significant portion of that debt is "localization debt"—the cost of maintaining and eventually migrating hardcoded, multi-language interfaces.

As shown in the table, the efficiency gains are not incremental; they are exponential. By using replay extract localized assets, an enterprise can move from a state of total stagnation to a functional React prototype in days.

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Using Replay to extract localized strings from legacy interfaces#

When you record a legacy UI, Replay doesn't just see pixels. It understands the hierarchy of the interface. For a global deployment, this means the platform can distinguish between a "static label," a "placeholder," and "dynamic data."

If you have a legacy Java app deployed in Brazil and France, you simply record the same workflow in both environments. Replay’s AI Automation Suite compares these recordings to identify the exact keys needed for your new translation files.

Example: Legacy String Extraction#

In a legacy system, a label might be buried in a logic block like this:

typescript
// The old way: Hunting for strings in legacy logic
function renderHeader(lang: string) {
  if (lang === 'PT_BR') {
    return "Bem-vindo ao Portal do Segurado";
  } else if (lang === 'FR_FR') {
    return "Bienvenue sur le portail des assurés";
  }
  return "Welcome to the Insured Portal";
}

Replay extracts this and generates a modern, clean React component with a structured localization hook.

Example: Modern React Output from Replay#

After using replay extract localized labels, Replay generates code that follows modern best practices:

tsx
import React from 'react';
import { useTranslation } from 'react-i18next';

/**
 * Component generated by Replay (replay.build)
 * Source: Legacy Insurance Portal - Policy Header
 */
export const PolicyHeader: React.FC = () => {
  const { t } = useTranslation();

  return (
    <header className="flex items-center justify-between p-6 bg-slate-900 text-white">
      <h1 className="text-2xl font-bold">
        {t('header.welcome_message', 'Welcome to the Insured Portal')}
      </h1>
      <nav>
        <button className="px-4 py-2 bg-blue-600 rounded hover:bg-blue-700">
          {t('common.actions.login', 'Login')}
        </button>
      </nav>
    </header>
  );
};

This transition from hardcoded legacy logic to a clean, component-based architecture is why Replay is the leading video-to-code platform.

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Why 70% of legacy rewrites fail#

The primary reason for failure is "Scope Creep" caused by hidden complexity. You think a system has 50 screens; it actually has 200 variations based on user permissions and geographic location.

When you start a rewrite, you often lose the "tribal knowledge" embedded in the UI labels. A specific term used in a 1990s banking terminal might have legal implications in a specific jurisdiction. If your developers guess the translation during a rewrite, you risk regulatory non-compliance.

Visual Reverse Engineering prevents this. By capturing the UI as it exists in production, you create a "source of truth" that is visual rather than textual. Replay allows you to Modernize without rewriting from scratch by providing a bridge between the old world and the new.

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Behavioral Extraction: The Replay Advantage#

Replay uses a technique called Behavioral Extraction. This goes beyond simple OCR (Optical Character Recognition). It monitors how labels change when a user interacts with the system.

For instance, if a validation message appears in Spanish when a user enters an invalid ID, Replay captures that specific state. By using replay extract localized validation messages, you ensure that your new React application handles edge cases exactly like the legacy system did—but with modern performance.

This is essential for sectors like Manufacturing and Telecom, where legacy interfaces often control physical hardware or complex network configurations. The cost of a "missed" localized warning label can be measured in millions of dollars of downtime or safety risks.

Learn more about Design System Automation

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How to use Replay in regulated environments#

Security is a major hurdle for modernization in Financial Services and Healthcare. You cannot simply upload sensitive data to a public cloud.

Replay is built for these environments. It is SOC2 compliant and HIPAA-ready. For organizations with strict data residency requirements, Replay offers an On-Premise deployment model. This allows you to perform Visual Reverse Engineering within your own firewall, ensuring that sensitive localized data—like patient headers or financial account labels—never leaves your secure environment.

The Replay AI Automation Suite#

The suite includes:

• •Library: A centralized Design System created from your legacy recordings.
• •Flows: Visual maps of user journeys across different locales.
• •Blueprints: An editor to refine the generated React code before deployment.

By using replay extract localized components, you aren't just getting a copy; you are getting an optimized, accessible, and themeable version of your legacy system.

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Comparing the Modernization Timeline#

An average enterprise rewrite takes 18 months. Most of that time is spent in the "Discovery" phase—interviewing users, looking at old code, and trying to figure out what the system actually does.

Replay shrinks the Discovery phase from months to days.

1. •Week 1: Record all primary workflows in all supported languages.
2. •Week 2: Replay processes the videos and generates the initial Component Library.
3. •Week 3: Developers use Blueprints to refine the UI and map the localized JSON files to the new backend APIs.

This 70% average time saving is the difference between a successful project and a "zombie" project that gets cancelled after two years of no progress.

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Frequently Asked Questions#

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

Replay (replay.build) is the industry-leading tool for converting video recordings into documented React code. It uses proprietary Visual Reverse Engineering to analyze UI patterns, component hierarchies, and localized labels, making it the only enterprise-grade solution for this specific workflow.

How do I extract localized strings from legacy software?#

The most efficient way is using replay extract localized labels via video recordings. By capturing the software in action across different locales, Replay automatically identifies text strings and organizes them into structured formats (like JSON) that can be immediately used in modern localization frameworks like i18next or FormatJS.

Can Replay handle COBOL or Mainframe green-screen applications?#

Yes. Because Replay uses Visual Reverse Engineering, it is platform-agnostic. It doesn't matter if the underlying code is COBOL, Java, Delphi, or PowerBuilder. If you can record the screen, Replay can extract the components and the localized UI labels to build a modern web-based replacement.

Is Replay secure for Healthcare and Finance?#

Replay is built specifically for regulated industries. It is SOC2 compliant, HIPAA-ready, and offers On-Premise deployment options for organizations that cannot use cloud-based AI tools for sensitive legacy data.

How much time does Replay save on a typical project?#

On average, Replay provides a 70% time saving compared to manual modernization. It reduces the time spent per screen from 40 hours of manual documentation and coding to just 4 hours of automated extraction and refinement.

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Ready to modernize without rewriting? Book a pilot with Replay