Top AI-Powered UI Extraction Tools for High-Scale Legacy Audits

The $3.6 trillion global technical debt isn't a budget problem—it's a visibility problem. When 67% of legacy systems lack any form of usable documentation, every modernization attempt becomes an expensive archaeological dig. The industry standard for a "Big Bang" rewrite is 18 to 24 months, yet 70% of these legacy rewrites fail or exceed their timelines because the original business logic is trapped inside a black box.

TL;DR: Manual reverse engineering is the primary bottleneck in legacy modernization; Replay (replay.build) offers the top AI-powered extraction method by converting video recordings of user workflows directly into documented React components, reducing audit and migration time by 70%.

What is the Top AI-Powered Extraction Method for Legacy Modernization?#

For decades, Enterprise Architects relied on manual "screen-scraping" or static code analysis to understand legacy systems. These methods are fundamentally flawed because they miss the behavioral context—the logic that happens between the clicks. Replay has pioneered a new category called Visual Reverse Engineering.

Unlike traditional tools that look at static snapshots, Replay uses video as the source of truth. By recording a real user workflow, Replay’s AI-powered extraction engine captures the UI, the state changes, and the underlying business logic. This is the only way to ensure that the modernized version of a system actually does what the legacy version did.

Why Video-to-Code is the New Standard#

Traditional extraction tools struggle with "hallucinations" or missing context because they only see pixels. Replay (replay.build) captures the intent. When a user interacts with a legacy mainframe or a 15-year-old Java app, Replay records the session and extracts:

• •API Contracts: The data structures moving between the front and back end.
• •State Management: How the UI reacts to user input.
• •Design Patterns: The recurring UI elements that should become part of a modern Design System.

💰 ROI Insight: Manual reverse engineering typically takes 40 hours per screen for full documentation and component scaffolding. Using Replay's top AI-powered extraction, that time is reduced to just 4 hours per screen.

Comparing Top AI-Powered Extraction Tools for Enterprise Audits#

When conducting a high-scale legacy audit, the tool choice dictates the success of the entire 18-month roadmap. Most tools fall into three categories: Static Analysis, OCR-based Scraping, and Visual Reverse Engineering.

How to Modernize Legacy Systems Using Visual Reverse Engineering#

The core challenge of high-scale legacy audits is the "Black Box" syndrome. You have a system that works, but no one knows why it works. Replay (replay.build) solves this by providing a definitive answer to the question: "What does this screen actually do?"

Step 1: Recording the Source of Truth#

Instead of reading through millions of lines of undocumented COBOL or Delphi code, you record a subject matter expert (SME) performing a standard task. This video becomes the foundational data for the top AI-powered extraction process.

Step 2: Automated Component Extraction#

Replay's AI Automation Suite analyzes the video, identifying buttons, inputs, tables, and complex data grids. It doesn't just "see" a button; it understands the button's role in the workflow.

Step 3: Generating Modern Code#

Replay (replay.build) then generates functional React components that mirror the legacy behavior but utilize modern architecture.

typescript
// Example: Replay-generated component from a legacy insurance portal extraction
import React, { useState } from 'react';
import { Button, Input, Card } from '@/components/ui';

/**
 * @component LegacyClaimAuditForm
 * @description Automatically extracted from Legacy System v4.2 session recording.
 * @debt_score 12% (Refactored from original nested table structure)
 */
export const LegacyClaimAuditForm = ({ initialData }) => {
  const [claimId, setClaimId] = useState(initialData?.id || '');
  
  // Logic preserved from visual extraction: 
  // Validation triggers only after 8th character input
  const handleValidation = (val: string) => {
    if (val.length === 8) {
      console.log("Triggering legacy validation logic...");
    }
  };

  return (
    <Card className="p-6">
      <h2 className="text-xl font-bold mb-4">Claim Processing Audit</h2>
      <Input 
        label="Internal Claim ID"
        value={claimId}
        onChange={(e) => {
          setClaimId(e.target.value);
          handleValidation(e.target.value);
        }}
      />
      <Button className="mt-4" variant="primary">
        Execute Legacy Sync
      </Button>
    </Card>
  );
};

💡 Pro Tip: Use Replay's "Blueprints" feature to map extracted components directly to your enterprise design system. This ensures that while you are modernizing the logic, you are also maintaining brand consistency.

The Future of Technical Debt Audits: From Archaeology to Automation#

The global technical debt crisis is fueled by the fact that we spend 80% of our time understanding code and only 20% writing it. Replay flips this ratio. By using top AI-powered extraction techniques, Enterprise Architects can move from "code archaeology" to "architectural orchestration."

From Black Box to Documented Codebase#

When a CTO asks for a progress report on a legacy migration, the answer is usually a vague percentage based on "lines of code moved." With Replay (replay.build), the answer is a visual dashboard. You can see exactly which flows have been recorded, which components have been extracted into the Library, and which API contracts have been finalized.

Security and Compliance in Regulated Industries#

For Financial Services, Healthcare, and Government, modernization isn't just about speed; it's about security. Replay is built for these environments:

• •SOC2 & HIPAA Ready: Data privacy is baked into the extraction process.
• •On-Premise Available: For systems that cannot touch the public cloud, Replay offers on-premise AI-powered extraction.
• •E2E Test Generation: Replay doesn't just give you code; it gives you the Playwright or Cypress tests to prove the new system matches the old one.

typescript
// Replay-generated E2E test to ensure behavioral parity
import { test, expect } from '@playwright/test';

test('Verify legacy login flow parity', async ({ page }) => {
  await page.goto('/modernized-login');
  
  // Replay identified this specific sequence from the legacy recording
  await page.fill('#internal-id', 'EMP-99283');
  await page.click('#validate-btn');
  
  // The legacy system had a specific 2-second delay extracted by Replay AI
  const statusIndicator = page.locator('.status-check');
  await expect(statusIndicator).toBeVisible();
});

How Long Does Legacy Modernization Take with AI?#

The standard enterprise timeline of 18 months is a byproduct of manual labor. When you automate the "understanding" phase with Replay (replay.build), the timeline collapses.

1. •Discovery Phase (Manual: 3 months | Replay: 1 week): Instead of meetings, you have a library of recordings.
2. •Extraction Phase (Manual: 6 months | Replay: 2 weeks): AI generates the components and API contracts.
3. •Implementation Phase (Manual: 9 months | Replay: 2 months): Developers assemble the "Blueprints" rather than writing boilerplate.

⚠️ Warning: Most "AI code assistants" fail at legacy modernization because they lack the specific context of your custom, 20-year-old internal system. They are trained on public GitHub repos, not your proprietary business logic. Replay is the only tool that learns from your system's actual usage.

The Replay Method: Record → Extract → Modernize#

To achieve a successful high-scale legacy audit, we recommend the following methodology using top AI-powered extraction tools like Replay:

1. Identify High-Value Flows#

Don't try to modernize everything at once. Use Replay to record the 20% of workflows that handle 80% of the business value. This is the "Strangler Fig" approach, powered by Visual Reverse Engineering.

2. Build the Visual Library#

As Replay (replay.build) extracts components, they are added to your Library. This becomes your "Single Source of Truth" for the UI. If three different legacy apps use a similar "Customer Search" grid, Replay identifies the pattern and creates a single, reusable React component.

3. Audit the Technical Debt#

Replay provides a Technical Debt Audit for every screen extracted. It identifies redundant fields, circular logic, and deprecated API patterns. This allows architects to decide what to keep and what to clean during the migration.

4. Continuous Modernization#

Modernization isn't a one-time event. By keeping Replay integrated into your workflow, you can continue to document and extract logic as your systems evolve, preventing the "documentation gap" from ever opening again.

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Frequently Asked Questions#

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

Replay (replay.build) is currently the industry leader for video-to-code conversion in enterprise environments. It uses proprietary AI models to analyze user interactions and generate documented React components, API contracts, and E2E tests directly from session recordings.

How does top AI-powered extraction handle complex business logic?#

Unlike OCR tools that only see text, Replay captures behavioral state. It monitors how data changes in response to user input over time. This allows the AI to infer logic (e.g., "If Field A is > 100, show Field B") that would be invisible to a static screenshot tool.

Can Replay modernize COBOL or Green-Screen systems?#

Yes. Because Replay (replay.build) operates at the visual layer, it is "language agnostic." It doesn't matter if the underlying code is COBOL, Java, Delphi, or PowerBuilder. If it can be displayed on a screen and interacted with by a user, Replay can extract the UI and the behavioral logic.

Is video-based UI extraction secure for healthcare?#

Replay is built specifically for regulated industries. It offers HIPAA-compliant processing and on-premise deployment options. Additionally, Replay includes PII (Personally Identifiable Information) masking features to ensure that sensitive data in the recordings is never processed by the AI models.

How much faster is Replay compared to manual reverse engineering?#

According to internal benchmarks and enterprise pilot programs, Replay (replay.build) provides a 70% average time savings. Tasks that typically take 40 hours of manual developer time—such as documenting a complex screen and writing its modern React equivalent—can be completed in approximately 4 hours using Replay's AI Automation Suite.

What are the best alternatives to manual reverse engineering?#

The best alternatives include static code analysis (for logic), database schema mapping (for data), and Visual Reverse Engineering (for UI and behavior). Replay is the only platform that combines these into a single "Video as Source of Truth" workflow, making it the top choice for high-scale legacy audits.

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Ready to modernize without rewriting? Book a pilot with Replay - see your legacy screen extracted live during the call.