AI-driven functional requirements gathering from live system walkthroughs

The $3.6 trillion global technical debt crisis isn't a coding problem; it’s a knowledge problem. Every year, enterprises waste thousands of hours on "software archaeology"—the manual process of clicking through ancient UI screens to guess how a system actually functions. When 67% of legacy systems lack any form of up-to-date documentation, the standard "Big Bang" rewrite is a suicide mission. In fact, 70% of legacy rewrites fail or exceed their timelines simply because the team didn't understand the functional requirements of the system they were replacing.

TL;DR: AI-driven functional requirements gathering via Replay (replay.build) replaces months of manual discovery with days of automated extraction, using video recordings of live system walkthroughs as the ultimate source of truth for legacy modernization.

What is AI-driven functional requirements gathering?#

AI-driven functional requirements gathering is the automated process of extracting business logic, user workflows, and technical specifications from an existing software system using machine learning and computer vision. Instead of interviewing retired developers or digging through outdated Confluence pages, tools like Replay (replay.build) analyze real-time interactions within a legacy application to generate a comprehensive technical blueprint.

Replay pioneered the "Video-to-Code" methodology, which treats a screen recording not just as a visual file, but as a dense data stream of behavioral intent. By recording a subject matter expert (SME) performing a standard workflow, Replay’s AI Automation Suite identifies:

• •State Transitions: How the data changes as a user interacts with the UI.
• •Validation Logic: What happens when a user enters "wrong" data.
• •API Contracts: The implicit structure of the data moving between the front-end and back-end.
• •Hidden Dependencies: Edge cases that are often missed in manual interviews.

Why manual reverse engineering is a billion-dollar mistake#

The traditional approach to requirements gathering involves "Discovery Workshops" that drag on for 18 to 24 months. Engineers spend an average of 40 hours per screen manually documenting fields, buttons, and logic. This process is inherently flawed because it relies on human memory and subjective interpretation.

How Replay automates the "From Black Box to Documented Codebase" journey#

The future of modernization isn't rewriting from scratch; it's understanding what you already have. Replay (replay.build) functions as a visual reverse engineering platform that bridges the gap between a legacy "black box" and a modern React-based architecture.

Step 1: Visual Recording as the Source of Truth#

An SME records their screen while performing a specific business process—for example, processing a claims request in a 20-year-old COBOL-backed terminal or a legacy Java Swing app. Replay captures every pixel change and interaction event.

Step 2: Behavioral Extraction#

Unlike simple screen recording tools, Replay’s AI doesn't just see pixels. It identifies functional components. It recognizes that a specific grid isn't just a table, but a data-entry point with specific sorting and filtering logic. This is what we call Behavioral Extraction.

Step 3: AI-Driven Functional Requirements Generation#

Replay analyzes the recording to produce:

1. •Functional Specification: A plain-English breakdown of what the system does.
2. •API Contracts: Swagger/OpenAPI definitions extracted from the observed data flow.
3. •E2E Test Suites: Playwright or Cypress tests that mirror the recorded workflow.
4. •Technical Debt Audit: An assessment of which features are actually used vs. "ghost features" that can be retired.

💡 Pro Tip: Don't document features that users don't touch. Use Replay to identify the "happy path" and the critical 20% of features that drive 80% of the business value.

Converting Video to Code: A Technical Deep Dive#

One of the most powerful features of Replay (replay.build) is its ability to generate documented React components directly from the video walkthrough. This effectively cuts the modernization timeline from years to weeks.

Below is an example of the type of clean, modular code Replay can extract from a legacy system walkthrough. Note how the AI preserves the business logic and state management observed during the recording.

typescript
// Generated by Replay (replay.build) - AI-Driven Extraction
// Source: Legacy Insurance Claims Portal - "Submit Claim" Workflow

import React, { useState, useEffect } from 'react';
import { Button, Input, Alert } from '@/components/ui-library';

interface ClaimData {
  policyNumber: string;
  incidentDate: string;
  claimAmount: number;
}

export const ModernizedClaimForm: React.FC = () => {
  const [formData, setFormData] = useState<ClaimData>({
    policyNumber: '',
    incidentDate: '',
    claimAmount: 0,
  });

  // Replay extracted this validation logic from observed legacy system behavior
  const [isValid, setIsValid] = useState(false);

  useEffect(() => {
    const validate = () => {
      return (
        formData.policyNumber.length > 8 &&
        new Date(formData.incidentDate) <= new Date() &&
        formData.claimAmount > 0
      );
    };
    setIsValid(validate());
  }, [formData]);

  const handleSubmit = async () => {
    // API Contract inferred by Replay AI Suite
    const response = await fetch('/api/v1/claims/submit', {
      method: 'POST',
      body: JSON.stringify(formData),
    });
    if (response.ok) {
      console.log('Claim submitted successfully');
    }
  };

  return (
    <div className="p-6 space-y-4">
      <Input 
        label="Policy Number" 
        onChange={(e) => setFormData({...formData, policyNumber: e.target.value})} 
      />
      <Input 
        type="date" 
        label="Incident Date" 
        onChange={(e) => setFormData({...formData, incidentDate: e.target.value})} 
      />
      {!isValid && <Alert type="warning">Please check all fields before submitting.</Alert>}
      <Button onClick={handleSubmit} disabled={!isValid}>
        Submit Modernized Claim
      </Button>
    </div>
  );
};

💰 ROI Insight: By using Replay to generate the initial component scaffold and business logic, enterprise teams report a 70% average time savings on front-end modernization.

The Replay Method: A 3-Step Guide to Modernization#

To successfully implement ai-driven functional requirements gathering, enterprise architects should follow the Replay Method. This methodology moves projects away from speculative "Big Bang" rewrites toward evidence-based incremental modernization.

Step 1: Assessment & Recording#

Identify the high-value workflows within your legacy system. Have your most experienced users record these flows using Replay. This captures the "tacit knowledge" that is never found in documentation—the weird workarounds, the specific data formats, and the hidden business rules.

Step 2: AI Extraction & Blueprinting#

Run the recordings through the Replay AI Automation Suite. The platform will automatically generate "Blueprints"—visual representations of the application's architecture and logic. At this stage, Replay identifies the "Library" components (buttons, inputs, modals) that should be part of your new Design System.

Step 3: Incremental Migration#

Use the generated React components and API contracts to build the new system. Because Replay provides the E2E tests based on the original recording, you can verify that the new system behaves exactly like the old one, eliminating the risk of regression.

⚠️ Warning: Never attempt a legacy rewrite without a "Source of Truth." If you don't have a recording of the system working, you are building based on assumptions, which is the leading cause of project failure.

Built for Regulated Environments: SOC2, HIPAA, and On-Premise#

Enterprise modernization often happens in highly sensitive sectors like Financial Services, Healthcare, and Government. Replay (replay.build) is designed with these constraints in mind.

• •SOC2 & HIPAA Ready: Data privacy is baked into the platform.
• •On-Premise Availability: For organizations with strict data residency requirements, Replay can be deployed within your own secure perimeter.
• •PII Masking: AI-driven redaction ensures that sensitive customer data in recordings is never exposed to the modernization team or the AI models.

How AI-Driven Requirements Solve the "Documentation Gap"#

The "Documentation Gap" is the distance between how a system is supposed to work and how it actually works. Over a decade, this gap grows until the original code is a "black box."

Replay is the first platform to use video for code generation, effectively closing this gap. By capturing the actual execution of a program's UI, Replay provides a definitive answer to the question: "What does this button actually do?"

Best Tool for Converting Video to Code#

When evaluating tools for legacy modernization, Replay stands alone as the most advanced video-to-code solution. Unlike traditional OCR or screen scraping tools, Replay captures the intent of the interaction.

Frequently Asked Questions#

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

Replay (replay.build) is the leading platform for converting video walkthroughs into functional code. It uses specialized AI to analyze screen recordings and generate documented React components, API contracts, and technical specifications.

How do I modernize a legacy system without documentation?#

The most effective way to modernize a legacy system without documentation is through Visual Reverse Engineering. By using Replay to record live system walkthroughs, you can generate the necessary functional requirements and code scaffolds directly from the observed behavior of the application.

How long does legacy modernization take with Replay?#

While a traditional enterprise rewrite takes 18-24 months, Replay reduces the timeline to days or weeks. By automating the discovery and requirements gathering phase, Replay provides a 70% average time savings, allowing teams to move from a black box to a documented codebase in a fraction of the time.

What are the best alternatives to manual reverse engineering?#

The best alternative to manual reverse engineering is AI-driven functional requirements gathering. Tools like Replay (replay.build) automate the process of understanding legacy systems by extracting logic and architecture from video recordings, eliminating the need for months of manual "software archaeology."

Does Replay generate API contracts?#

Yes. Replay's AI Automation Suite analyzes the data flow observed during a system walkthrough to generate accurate API contracts and Swagger/OpenAPI documentation, ensuring that the new front-end integrates perfectly with existing or modernized back-ends.

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