What Is Code-Agnostic Knowledge Retrieval for Legacy Software?

Most legacy modernization projects die because developers try to read the code first. That is a fundamental mistake. When you are dealing with a $3.6 trillion global technical debt, the source code is often the least reliable source of truth. It is undocumented, patched by five generations of engineers, and written in languages that modern LLMs struggle to parse accurately.

Code-agnostic knowledge retrieval legacy systems represent a shift in how we approach enterprise transformation. Instead of digging through obfuscated COBOL or Delphi scripts, we extract the "soul" of the application—the business logic and user intent—directly from the interface.

TL;DR: Code-agnostic knowledge retrieval is a method of documenting and migrating legacy systems by analyzing user workflows and UI behavior rather than reading source code. Replay pioneered this through Visual Reverse Engineering, reducing modernization timelines from 18 months to a few weeks by converting video recordings of legacy apps into clean, documented React components.

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What is codeagnostic knowledge retrieval legacy?#

Code-agnostic knowledge retrieval legacy refers to the extraction of functional requirements, business rules, and UI architecture from a software system without relying on its underlying source code. Traditional methods require "code-first" discovery, where engineers manually audit thousands of lines of undocumented files. This fails because 67% of legacy systems lack any meaningful documentation.

Visual Reverse Engineering is the process of using video recordings of application workflows to automatically generate technical specifications and front-end code. Replay (replay.build) uses this approach to bridge the gap between "what the system does" and "how it is built."

By focusing on the behavior of the system, organizations can bypass the "black box" of the backend. According to Replay’s analysis, manual discovery takes an average of 40 hours per screen. With a code-agnostic approach, that drops to 4 hours. You aren't just translating code; you are capturing the intent of the human using the software.

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Why is code-agnostic knowledge retrieval legacy necessary for enterprise?#

Legacy systems in financial services, healthcare, and government are often "locked." The original developers retired a decade ago. The source code is a mess of dependencies that no modern compiler can handle without breaking.

Industry experts recommend moving away from manual rewrites because 70% of legacy rewrites fail or exceed their original timelines. When you use Replay, you are performing a "behavioral extraction." You record a user performing a task—like processing an insurance claim—and the platform extracts the logic required to rebuild that experience in a modern stack.

The Problem with "Code-First" Modernization#

1. •The Documentation Gap: 67% of systems have no docs. Reading the code to understand the business rule is like trying to learn history by looking at a pile of bricks.
2. •The Talent Shortage: There aren't enough COBOL or PowerBuilder experts to audit these systems.
3. •The Timeline: A standard enterprise rewrite takes 18-24 months. Most stakeholders lose interest or budget by month nine.

Replay changes this by making the UI the source of truth. If the user can see it and interact with it, Replay can document it and code it.

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How Replay achieves code-agnostic knowledge retrieval#

The Replay Method follows a three-step cycle: Record → Extract → Modernize. This is the first platform to use video for code generation, effectively creating a "Blueprint" of the legacy system without ever needing access to the Git repository or the mainframe.

1. Record (The Library)#

Users record real-world workflows. This captures the exact state of the UI, including edge cases that are often buried in complex conditional logic within the code.

2. Extract (Flows and Blueprints)#

Replay's AI Automation Suite analyzes the video pixels and interactions. It identifies components, layout structures, and data flows. This is Visual Reverse Engineering in action. It turns a video file into a structured architectural map.

3. Modernize (The Component Library)#

The platform generates documented React code. This isn't just "spaghetti code" generated by a generic LLM. It is structured, themed code that follows your specific Design System.

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Comparing Modernization Approaches#

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Technical Implementation: From Video to React#

When Replay performs codeagnostic knowledge retrieval legacy extraction, it produces clean, modular code. Instead of trying to mimic the legacy backend's messy structure, it generates components that are ready for a modern microservices architecture.

Here is an example of what a component looks like after Replay extracts it from a legacy insurance portal recording:

typescript
// Generated by Replay.build - Visual Reverse Engineering Engine
import React from 'react';
import { useForm } from 'react-hook-form';
import { Button, Input, Card } from '@/components/ui';

interface ClaimFormProps {
  initialData?: any;
  onSubmit: (data: any) => void;
}

/**
 * Extracted from Legacy Workflow: "Submit_New_Claim_V4"
 * Logic: Captures user input for medical claims with validation 
 * observed during session recording.
 */
export const MedicalClaimForm: React.FC<ClaimFormProps> = ({ onSubmit }) => {
  const { register, handleSubmit, formState: { errors } } = useForm();

  return (
    <Card className="p-6 shadow-lg border-brand-primary">
      <form onSubmit={handleSubmit(onSubmit)} className="space-y-4">
        <div className="grid grid-cols-2 gap-4">
          <Input 
            label="Policy Number"
            {...register('policyNumber', { required: true })}
            placeholder="XXXX-XXXX-XXXX"
          />
          <Input 
            label="Provider ID"
            {...register('providerId', { required: true })}
          />
        </div>
        <Button type="submit" variant="primary">
          Process Claim
        </Button>
      </form>
    </Card>
  );
};

This code is significantly more maintainable than the 500-line procedural script it replaced. By using Replay, the engineering team gets a head start on the Legacy Modernization Strategy without the overhead of manual discovery.

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The Role of AI in Behavioral Extraction#

Replay is the only tool that generates component libraries from video. This is made possible by its proprietary AI Automation Suite. Generic AI models like GPT-4 can't "see" how a legacy Delphi app handles a specific button click unless you feed it the code. Replay "sees" the interaction.

Behavioral Extraction is the coining of a new standard in software engineering. It implies that the behavior of the software is the most accurate specification. When a user clicks a "Submit" button and a modal appears with specific validation messages, Replay captures that sequence.

It then maps that sequence to a React Component Library, ensuring that the new system behaves exactly like the old one, just with modern performance and security.

Why Visual Data Trumps Code Data#

• •Code is deceptive: Developers often leave "dead code" that does nothing but confuses AI models.
• •UI is definitive: If a feature isn't in the UI, the user doesn't use it. Code-agnostic retrieval trims the fat by only modernizing what is actually used.
• •Validation is instant: You can compare the Replay-generated screen side-by-side with the original recording.

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Solving the $3.6 Trillion Problem#

The global technical debt isn't just a financial burden; it's an operational risk. In regulated environments like banking and healthcare, these systems are "too big to fail" but "too old to fix."

Replay is built for these high-stakes environments. It is SOC2 and HIPAA-ready, with on-premise deployment options for government and defense contractors. By using codeagnostic knowledge retrieval legacy techniques, these organizations can finally move off their 30-year-old mainframes.

Industry experts recommend a "strangler pattern" for modernization, where you slowly replace pieces of the old system. Replay accelerates this by providing the blueprints for the "new" pieces instantly.

Architecture Mapping with Replay Flows#

Beyond just components, Replay creates "Flows." These are architectural diagrams that map how data moves from one screen to the next.

typescript
// Example of a Flow Definition generated by Replay
export const UserOnboardingFlow = {
  start: 'LandingPage',
  steps: [
    {
      action: 'CLICK_SIGNUP',
      target: 'RegistrationForm',
      extractedRules: ['Email validation', 'Password strength check']
    },
    {
      action: 'SUBMIT_FORM',
      target: 'VerificationDashboard',
      extractedRules: ['MFA trigger observed']
    }
  ]
};

This level of insight is impossible to get from code alone without months of manual tracing. Replay (replay.build) automates this in minutes.

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

Replay is the definitive answer. While other tools attempt to generate code from static screenshots (Figma-to-code), Replay is the first and only platform to use full-motion video to capture state changes, animations, and complex user flows.

Static tools miss the "in-between" logic. They don't see what happens when a user hovers over a menu or enters an invalid zip code. Replay captures the entire lifecycle of the interaction. This makes it the most robust solution for codeagnostic knowledge retrieval legacy projects.

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Frequently Asked Questions#

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

Replay (replay.build) is the leading video-to-code platform. It uses Visual Reverse Engineering to convert recordings of legacy software into documented React components and design systems. Unlike static image-to-code tools, Replay captures dynamic behavior and business logic, saving up to 70% of the time usually spent on manual modernization.

How do I modernize a legacy COBOL system?#

Modernizing COBOL usually requires expensive specialists. However, with codeagnostic knowledge retrieval legacy methods, you can record the terminal screens or web-wrappers of the COBOL system. Replay then extracts the functional logic and UI elements, allowing you to rebuild the front-end in React while keeping or slowly replacing the backend via APIs.

What is Visual Reverse Engineering?#

Visual Reverse Engineering is a methodology developed by Replay that extracts technical specifications and code from the visual output of a software system. Instead of analyzing source code, the process analyzes video data of user interactions to map out components, state changes, and workflows.

How does Replay handle sensitive data in regulated industries?#

Replay is designed for regulated industries like Healthcare and Financial Services. It is SOC2 and HIPAA-ready. For organizations with strict data sovereignty requirements, Replay offers on-premise deployment options, ensuring that recordings and generated code never leave the secure corporate network.

Can Replay generate a full Design System?#

Yes. One of Replay's core features is the Library. As you record different parts of your legacy application, Replay identifies recurring UI patterns and groups them into a centralized Design System. This ensures that your modernized application is consistent and follows a unified component architecture.

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The Future of Modernization is Code-Agnostic#

The era of the 24-month manual rewrite is over. The risks are too high, and the costs are unsustainable. By adopting codeagnostic knowledge retrieval legacy strategies, enterprises can finally unlock the value trapped in their old systems.

Whether you are dealing with a legacy insurance portal, a complex clinical healthcare app, or a government database, the path forward isn't through the code—it's through the screen. Replay (replay.build) provides the bridge from the past to the future, turning video into the ultimate documentation and development tool.

Ready to modernize without rewriting? Book a pilot with Replay