AI-Powered Reverse Engineering: How Video Analysis Generates Production-Ready React

The most expensive code in your enterprise is the code nobody understands.

Global technical debt has ballooned to an estimated $3.6 trillion, and for most Fortune 500 companies, the strategy for dealing with it remains fundamentally broken. We treat legacy modernization as a "Big Bang" event—a high-stakes, 18-to-24-month rewrite that carries a 70% failure rate. When these projects fail, they don't just lose money; they paralyze the roadmap, burn out top talent, and leave the organization tethered to crumbling infrastructure.

The bottleneck isn't the coding. It's the archaeology. With 67% of legacy systems lacking any meaningful documentation, engineers spend 80% of their time "reading the pixels"—manually tracing execution paths and reverse-engineering business logic from undocumented COBOL, Delphi, or early Java monoliths.

AI-powered reverse engineering via video analysis changes this calculus. By using video as the source of truth, we can bypass the "black box" problem and generate production-ready React components in days rather than months.

TL;DR: AI-powered reverse engineering uses video analysis of real user workflows to automatically extract business logic, state transitions, and UI structures, reducing modernization timelines by 70%.

The Failure of Manual Archaeology#

The traditional approach to modernization involves a "discovery phase" that often lasts six months. Architects sit with subject matter experts (SMEs), take screenshots, and write Jira tickets that attempt to describe complex state machines.

This process is inherently lossy. A manual audit of a single enterprise screen takes an average of 40 hours when you account for:

1. •Mapping API dependencies.
2. •Identifying hidden conditional logic.
3. •Documenting edge-case validation rules.
4. •Designing a modern equivalent in Figma.

In contrast, Replay reduces this to 4 hours per screen. By recording the actual execution of the workflow, the platform captures the "ground truth" of how the system behaves, not just how someone remembers it works.

Modernization Methodology Comparison#

From Video to React: The Technical Mechanism#

How does a video recording become a production-ready React component? It isn't just "OCR for code." It’s a multi-layered extraction process that combines computer vision, network interception, and Large Language Models (LLMs) specialized in architectural patterns.

1. Visual Primitive Extraction#

Replay analyzes the video frames to identify UI primitives. It distinguishes between a static label and a dynamic input, mapping visual hierarchies to a clean DOM structure. This isn't just generating <div> soup; it’s identifying that a specific cluster of pixels represents a "Searchable Dropdown" or a "Data Grid with Pagination."

2. State and Logic Mapping#

While the video captures the UI, Replay’s AI Automation Suite monitors the underlying state transitions. If a user clicks "Submit" and a specific error message appears, the AI correlates that visual event with the intercepted API call and the resulting JSON payload.

3. Code Generation (The Blueprint)#

The platform then synthesizes these observations into a "Blueprint." This is a structured representation of the component's intent. The resulting React code is modular, typed with TypeScript, and integrated into your organization's specific Design System.

typescript
// Example: Replay-generated component from a legacy insurance claims screen
import React, { useState, useEffect } from 'react';
import { Button, Input, Alert, Card } from '@/components/ui-library';
import { useClaimsProcessor } from '@/hooks/useClaims';

/**
 * @generated Generated via Replay Visual Reverse Engineering
 * Source: Legacy Claims Portal - Screen ID: 099-X
 * Logic: Validates claim ID format and checks real-time eligibility
 */
export const ClaimValidationModule: React.FC = () => {
  const [claimId, setClaimId] = useState<string>('');
  const [status, setStatus] = useState<'idle' | 'loading' | 'success' | 'error'>('idle');
  const { validateClaim, error } = useClaimsProcessor();

  // Logic extracted from legacy behavior: 
  // System requires 12-digit alphanumeric input with 'CLM' prefix
  const handleValidation = async () => {
    if (!claimId.startsWith('CLM') || claimId.length < 12) {
      setStatus('error');
      return;
    }
    setStatus('loading');
    await validateClaim(claimId);
    setStatus('success');
  };

  return (
    <Card title="Claim Verification">
      <div className="space-y-4">
        <Input 
          label="Enter Claim ID"
          value={claimId}
          onChange={(e) => setClaimId(e.target.value)}
          placeholder="CLM-000-000-00"
        />
        {status === 'error' && (
          <Alert variant="destructive">Invalid Claim Format Detected</Alert>
        )}
        <Button 
          onClick={handleValidation}
          loading={status === 'loading'}
        >
          Verify Eligibility
        </Button>
      </div>
    </Card>
  );
};

⚠️ Warning: Never trust AI-generated code that lacks a visual source of truth. Without recording the actual user flow, LLMs often "hallucinate" business logic that doesn't exist in the legacy system.

The 4-Step Modernization Pipeline#

For Enterprise Architects, the goal isn't just to get code—it's to get the right code into production. Replay follows a structured pipeline that ensures fidelity and maintainability.

Step 1: Recording and Ingestion#

SMEs or QA engineers record themselves performing critical business workflows in the legacy application. Replay captures the DOM state, network requests, and visual changes. This creates a "Source of Truth" that replaces outdated Confluence pages.

Step 2: Extraction and Blueprinting#

The Replay AI Automation Suite processes the recording. It generates:

• •API Contracts: Swagger/OpenAPI specs based on intercepted traffic.
• •State Machine Diagrams: Visualizing how the UI moves from one state to another.
• •Component Hierarchy: Breaking the screen down into reusable React components.

Step 3: Refinement in the Editor#

Using the Blueprints editor, architects can refine the generated code. You can map generic components to your internal Design System (e.g., mapping a legacy button to your

component in your Replay Library).

Step 4: E2E Test Generation#

One of the most significant risks in modernization is regression. Replay automatically generates Playwright or Cypress tests based on the recorded video.

typescript
// Generated Playwright Test to ensure parity between Legacy and Modern
import { test, expect } from '@playwright/test';

test('Claim validation flow parity check', async ({ page }) => {
  await page.goto('/claims/verify');
  
  // Replay captured this specific sequence of interactions
  await page.fill('input[name="claimId"]', 'CLM1234567890');
  await page.click('button[type="submit"]');
  
  // Asserting the extracted business logic outcome
  const successMessage = page.locator('.status-success');
  await expect(successMessage).toBeVisible();
  await expect(successMessage).toContainText('Eligibility Confirmed');
});

💰 ROI Insight: By automating E2E test generation during the extraction phase, companies save an average of 120 hours of QA engineering per module.

Solving the "Documentation Gap"#

The primary reason legacy systems become "black boxes" is the loss of institutional knowledge. When the original developers leave, the code becomes a liability.

Replay doesn't just modernize; it documents. Every extracted component is linked back to the original video recording. If a developer in 2026 wonders why a specific validation rule exists, they can watch the original 2024 recording of the legacy system to see the logic in action. This "Visual Documentation" reduces the cognitive load on new hires and prevents the accumulation of future technical debt.

Key Features for Regulated Industries#

For Financial Services, Healthcare, and Government sectors, "moving fast" cannot come at the expense of security.

• •On-Premise Availability: Replay can be deployed within your VPC, ensuring that sensitive data never leaves your perimeter.
• •SOC2 & HIPAA Ready: The platform is built to handle PII/PHI, with automated masking of sensitive data during the video analysis phase.
• •Technical Debt Audit: Replay provides a comprehensive audit of the legacy system's complexity before you write a single line of code, allowing for better resource allocation.

The Future of the Enterprise Architect#

The role of the Enterprise Architect is shifting from "Documenter-in-Chief" to "Orchestrator of AI Systems." We can no longer afford to spend months in the discovery phase. The $3.6 trillion technical debt mountain is growing faster than we can manually climb it.

By leveraging AI-powered reverse engineering, we turn the modernization process from a speculative gamble into a predictable engineering discipline. We move from "archaeology" to "extraction," and from "rewriting" to "evolving."

💡 Pro Tip: Start with your most stable, high-value workflows. Use Replay to extract these "low-hanging fruit" to demonstrate immediate ROI (70% time savings) to stakeholders before tackling the more volatile core monolith.

Frequently Asked Questions#

How does Replay handle complex business logic that isn't visible in the UI?#

Replay doesn't just look at the pixels; it intercepts the network layer and analyzes the data structures being passed back and forth. By observing how the UI reacts to specific data payloads, the AI can infer underlying business rules. For logic that is purely server-side (e.g., a COBOL calculation), Replay generates the API contract so your modern React frontend can interface with the existing backend logic via the Strangler Fig pattern.

Can we use our own Design System?#

Yes. Replay’s Library feature allows you to upload your existing React component library. During the extraction process, you can "map" legacy elements to your modern components. The AI learns these mappings, ensuring that all subsequent extractions use your organization's specific styling and props.

What is the learning curve for the engineering team?#

Because Replay generates standard TypeScript/React code and E2E tests, the learning curve is minimal. Your engineers continue to work in their preferred IDEs. Replay simply provides them with a 70% head start by handling the initial discovery, component structure, and boilerplate generation.

How long does a typical pilot project take?#

A standard pilot with Replay usually lasts 2–4 weeks. During this time, we typically modernize 5–10 complex screens, establish the API contracts, and generate the initial E2E test suite. This provides enough data to project the timeline for the full application modernization.

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