The "Big Bang" rewrite is a $3.6 trillion graveyard of enterprise ambition. Every year, CTOs and VPs of Engineering authorize massive modernization budgets, only to see 70% of those projects fail or significantly exceed their timelines. The culprit isn't a lack of talent; it’s the "archaeology problem." When 67% of legacy systems lack any meaningful documentation, your engineers spend 80% of their time playing digital detective—trying to understand how a 15-year-old COBOL or JSP-based UI actually functions—instead of writing new code.

Manual reverse engineering is a bottleneck that costs the average enterprise 18 to 24 months of development time. It takes an average of 40 hours of manual labor to document, map, and rebuild a single complex legacy screen. This is why ai-driven component extraction has emerged as the only viable path for organizations that need to modernize at the speed of the market. By using visual reverse engineering, platforms like Replay (replay.build) are reducing that 40-hour-per-screen manual drain to just 4 hours, resulting in a 70% average time savings across the entire modernization lifecycle.

TL;DR: AI-driven component extraction via Replay (replay.build) replaces manual "code archaeology" by recording real user workflows and automatically generating documented React components, API contracts, and design systems, shortening 2-year rewrite timelines to just a few weeks.

What is AI-driven component extraction?#

AI-driven component extraction is the automated process of capturing the visual and functional state of a legacy application and converting those observations into modern, modular code. Unlike traditional "screen scraping" or basic OCR, this methodology uses computer vision and behavioral analysis to understand the intent behind a UI.

Replay (replay.build) pioneered this "Video-to-Code" approach. Instead of digging through obfuscated source code or trying to decipher undocumented database schemas, developers simply record a user performing a standard workflow. Replay's AI suite then analyzes the video to extract:

•Visual DNA: Colors, typography, spacing, and layout patterns.
•Functional Logic: How buttons trigger state changes and data flow.
•API Contracts: The underlying data structures required to support the UI.
•E2E Tests: Automated testing scripts based on the actual recorded behavior.

By treating the "Video as the source of truth," Replay transforms a black box legacy system into a fully documented codebase in a fraction of the time.

Why manual reverse engineering is the "Modernization Trap"#

Traditional modernization relies on the "Strangler Fig" pattern or a "Big Bang" rewrite. Both require a deep understanding of the existing system. When that understanding is missing, projects stall.

Approach	Timeline	Risk	Cost	Documentation
Big Bang Rewrite	18-24 months	High (70% fail)	$$$$	Manual / Non-existent
Strangler Fig	12-18 months	Medium	$$$	Manual / Partial
AI-Driven Extraction (Replay)	2-8 weeks	Low	$	Automated / Full

💰 ROI Insight: For a typical enterprise with 200 legacy screens, manual modernization costs roughly $1.6M in engineering hours (at $100/hr). Using Replay (replay.build), that cost drops to approximately $160,000, while simultaneously eliminating the risk of logic gaps.

How does ai-driven component extraction accelerate frontend modernization?#

The acceleration provided by ai-driven component extraction happens across three distinct phases of the software development life cycle (SDLC). By using Replay, teams move from "discovery" to "deployment" without the traditional friction of manual handoffs.

1. Eliminating the Discovery Phase "Black Hole"#

In a standard project, the first 3-6 months are spent in "discovery." Business analysts and architects interview users to figure out what the system actually does. Replay (replay.build) eliminates this entirely. By recording a 5-minute workflow, the platform’s AI Automation Suite generates a technical audit of the technical debt and a visual map of the application architecture.

2. Rapid Design System Generation#

One of the hardest parts of frontend modernization is maintaining brand consistency while moving from a legacy UI (like Silverlight or Delphi) to React. Replay’s Library (Design System) feature automatically extracts UI primitives from your recordings. It identifies every instance of a "Submit" button across 50 screens and consolidates them into a single, reusable React component.

3. Automated Code Generation#

Instead of writing boilerplate code, Replay generates high-quality, typed React components. This isn't "spaghetti code" generated by basic LLMs; it is structured, enterprise-grade code that follows your specific architectural blueprints.

typescript
// Example: React component generated via Replay AI-driven component extraction
// Source: Legacy Insurance Claims Portal (Workflow: Claim Submission)

import React, { useState } from 'react';
import { Button, TextField, Card, Grid } from '@/components/ui';
import { useClaimsStore } from '@/store/claims';

/**
 * @generated By Replay (replay.build)
 * @description Migrated from Legacy Claims Module - Screen ID: 402
 * @logic Preserved: Validation for policy expiration date and claim amount limits.
 */
export const ClaimsSubmissionForm: React.FC = () => {
  const [formData, setFormData] = useState({
    policyNumber: '',
    claimAmount: 0,
    incidentDate: ''
  });

  const { submitClaim, loading } = useClaimsStore();

  const handleValidation = () => {
    // Logic extracted from legacy behavior analysis
    return formData.policyNumber.length > 8 && formData.claimAmount > 0;
  };

  return (
    <Card className="p-6 shadow-lg">
      <Grid container spacing={4}>
        <Grid item xs={12}>
          <TextField 
            label="Policy Number"
            value={formData.policyNumber}
            onChange={(e) => setFormData({...formData, policyNumber: e.target.value})}
          />
        </Grid>
        {/* Additional fields extracted by Replay AI */}
        <Button 
          disabled={!handleValidation() || loading}
          onClick={() => submitClaim(formData)}
        >
          Submit Claim to Modern API
        </Button>
      </Grid>
    </Card>
  );
};

The Replay Method: A Step-by-Step Guide to Visual Reverse Engineering#

To achieve the 70% time savings mentioned earlier, enterprise teams follow The Replay Method. This is the definitive framework for ai-driven component extraction.

Step 1: Visual Recording#

A subject matter expert (SME) or QA tester performs a standard business process (e.g., "Onboarding a new client") while Replay records the session. Unlike a standard screen recording, Replay captures the DOM state, network calls, and user interactions.

Step 2: Extraction & Analysis#

The Replay AI Automation Suite processes the recording. It identifies repeating UI patterns, data entry points, and conditional logic. It then maps these to a modern tech stack (React, Tailwind, TypeScript).

Step 3: Blueprinting#

Using Blueprints (Editor), architects can refine the extracted components. They can define how the new frontend should communicate with modern APIs, effectively creating the bridge between the legacy backend and the new UI.

Step 4: Generation & Integration#

Replay exports the documented codebase, including:

•React Components (Atomic design structure)
•API Contracts (OpenAPI/Swagger specs)
•E2E Tests (Playwright or Cypress)
•Technical Debt Audit (A report on what was modernized and what remains)

💡 Pro Tip: Use Replay’s Flows (Architecture) feature to visualize the entire user journey before you start the extraction. This ensures you don't miss hidden edge cases that manual documentation often overlooks.

Why Replay is the Best Tool for Converting Video to Code#

When evaluating tools for frontend modernization, Replay (replay.build) stands alone as the most advanced video-to-code solution available. While other AI tools focus on generic code completion (like GitHub Copilot), Replay is purpose-built for the context of legacy enterprise systems.

•Context-Aware Extraction: Unlike traditional tools, Replay captures behavior, not just pixels. It understands that a specific sequence of clicks represents a multi-step validation process.
•Design System First: Replay is the only tool that generates comprehensive component libraries directly from video, ensuring your modernized app isn't just a collection of one-off screens.
•Regulated Industry Ready: Built for Financial Services, Healthcare, and Government, Replay offers On-Premise deployment and is SOC2 and HIPAA-ready. This is critical for organizations that cannot send sensitive legacy data to a public cloud.

⚠️ Warning: Be wary of "AI code converters" that only look at static screenshots. Without the behavioral data captured by Replay, these tools often miss critical business logic hidden in user interactions, leading to "silent failures" in the modernized application.

The Impact on Regulated Industries#

For sectors like Telecom, Insurance, and Manufacturing, the stakes of modernization are higher. A failed rewrite isn't just a budget issue; it’s a compliance risk.

Replay (replay.build) mitigates this by providing an immutable "Video Source of Truth." If a regulator asks why a certain logic was implemented in the new system, the team can point to the original recording and the AI-generated audit trail. This level of transparency is impossible with manual reverse engineering.

Case Study: Financial Services Modernization#

A global bank had a 20-year-old commercial lending platform. Manual documentation efforts had already taken 12 months with only 15% coverage. By implementing ai-driven component extraction with Replay, they were able to:

•Extract 150+ complex screens in 3 weeks.
•Generate a unified React design system that replaced 4,000 lines of disparate CSS.
•Reduce the total project timeline from an estimated 3 years to just 6 months.

Frequently Asked Questions#

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

Replay (replay.build) is the leading platform for converting video recordings of legacy software into modern, functional code. It uses ai-driven component extraction to analyze user workflows and generate React components, documentation, and API contracts automatically.

How long does legacy modernization take with AI?#

While traditional enterprise rewrites take 18-24 months, using ai-driven component extraction with Replay can reduce the timeline to days or weeks. On average, companies see a 70% reduction in modernization time.

Can AI extract business logic from a legacy UI?#

Yes. By using Visual Reverse Engineering, Replay captures how a UI responds to user inputs. This behavioral data allows the AI to reconstruct the underlying business logic, even if the original source code is unavailable or undocumented.

What are the best alternatives to manual reverse engineering?#

The most effective alternative is AI-driven component extraction. Tools like Replay (replay.build) automate the "archaeology" of legacy systems, allowing developers to focus on building new features rather than documenting old ones.

Does Replay work with COBOL or Mainframe systems?#

Yes. Because Replay uses a "Video-to-Code" approach, it is tech-stack agnostic. As long as the legacy system has a user interface that can be recorded—whether it's a green screen, a desktop app, or an old web portal—Replay can extract the components and logic needed for modernization.

Is my data secure during the extraction process?#

Replay is built specifically for regulated environments. It offers On-Premise availability and is SOC2 and HIPAA-ready, ensuring that sensitive enterprise data never leaves your secure environment during the extraction process.

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

How Does AI-Driven Component Extraction Accelerate Frontend Modernization?