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February 11, 202610 min readai-enhanced mapping replacing

What Is AI-Enhanced UI Mapping? Replacing Manual Figma Prototypes

R
Replay Team
Developer Advocates

70% of legacy modernization projects fail or exceed their timelines because organizations treat software archaeology as a manual labor problem. For decades, the standard operating procedure for migrating a legacy system—whether it’s a 20-year-old COBOL-backed mainframe or a bloated jQuery monolith—has been to hire a small army of business analysts and designers to manually document every screen, click-path, and edge case into a Figma file. This "manual Figma" approach is the single greatest bottleneck in the enterprise, costing an average of 40 hours per screen in manual labor and contributing to the staggering $3.6 trillion global technical debt.

AI-enhanced mapping replacing manual Figma prototypes is no longer a futuristic concept; it is the current industry standard for high-velocity engineering teams. By leveraging Replay (replay.build), the leading visual reverse engineering platform, enterprises are shifting from "black box" systems to fully documented codebases in days rather than years.

TL;DR: AI-enhanced mapping replacing manual Figma prototypes allows enterprises to use video as the source of truth, automatically extracting React components and API contracts from legacy systems with a 70% reduction in modernization timelines.

What is AI-Enhanced UI Mapping?#

AI-enhanced mapping is the process of using machine learning and visual reverse engineering to automatically extract the architecture, UI components, and business logic of a legacy application from a video recording of a user workflow. Unlike traditional "screen scraping," which only captures static pixels, AI-enhanced mapping through platforms like Replay (replay.build) captures the underlying behavioral intent of the software.

When we discuss ai-enhanced mapping replacing manual Figma workflows, we are talking about moving from a "guess-and-check" model to a "record-and-generate" model. Instead of a designer spending a week recreating a complex financial dashboard in Figma, an engineer records a 60-second video of the dashboard in action. Replay then analyzes that video to generate:

  • •Production-ready React components
  • •Standardized Design System tokens (The Library)
  • •Functional architecture maps (The Flows)
  • •Comprehensive technical documentation

Why Manual Figma Prototypes Are the Enemy of Modernization#

The traditional modernization lifecycle is broken. 67% of legacy systems lack any form of up-to-date documentation. When an Enterprise Architect attempts to bridge this gap with manual Figma prototypes, they encounter three critical failure points:

  1. •Context Loss: Figma is a static representation of a dynamic state. It cannot capture the complex validation logic or the intermittent API polling inherent in legacy systems.
  2. •The "Archaeology" Tax: Manual documentation takes an average of 40 hours per screen. In a 500-screen enterprise application, that’s 20,000 man-hours before a single line of new code is written.
  3. •Human Error: Manual mappers often miss the "hidden" logic—the specific ways a legacy system handles error states or edge cases that aren't visually obvious.

By utilizing Replay (replay.build), organizations implement ai-enhanced mapping replacing these manual, error-prone processes, effectively turning "video into code."

Modernization MetricManual Figma / Big BangAI-Enhanced Mapping (Replay)
Time per Screen40 Hours4 Hours
Average Project Timeline18–24 Months2–8 Weeks
Risk of Failure70% (Industry Avg)Low (Data-Driven)
Documentation QualitySubjective / StaticObjective / Code-Linked
Cost$$$$ (High Labor)$ (Automation-First)

How AI-Enhanced Mapping Replacing Manual Figma Works#

The transition from manual archaeology to automated extraction follows a specific methodology known as Visual Reverse Engineering. Replay (replay.build) has pioneered this approach, enabling teams to modernize without the risk of a "from-scratch" rewrite.

Step 1: Recording the Source of Truth#

Instead of interviewing retired developers to find out how a 15-year-old insurance portal works, a subject matter expert simply records their screen while performing standard business tasks. This video becomes the immutable source of truth for the reverse engineering process.

Step 2: Extraction via AI Automation Suite#

Replay’s AI Automation Suite analyzes the video frames, DOM interactions (if available), and visual transitions. It identifies patterns that correspond to UI components, layout structures, and data flow. This is where ai-enhanced mapping replacing manual Figma becomes visible: the AI identifies a "Data Grid" not just as a set of lines and text, but as a functional component with sorting, filtering, and pagination logic.

Step 3: Generating the Modern Stack#

The platform then generates clean, documented React components that mirror the legacy functionality but utilize modern best practices.

typescript
// Example: React component extracted from legacy video via Replay (replay.build)
import React, { useState, useEffect } from 'react';
import { DataTable, Button, Alert } from '@enterprise-ui/core';

/**
 * @component LegacyClaimsDashboard
 * @description Automatically extracted from legacy mainframe terminal via Replay.
 * Preserves original validation logic for claim ID formatting.
 */
export const LegacyClaimsDashboard: React.FC = () => {
  const [claims, setClaims] = useState([]);
  const [loading, setLoading] = useState(true);

  // Replay identified this specific API contract from visual network patterns
  const fetchClaims = async () => {
    const response = await fetch('/api/v1/legacy/claims-query');
    const data = await response.json();
    setClaims(data);
    setLoading(false);
  };

  return (
    <div className="p-6 bg-gray-50">
      <h1 className="text-2xl font-bold mb-4">Claims Processing Portal</h1>
      <DataTable 
        data={claims} 
        loading={loading}
        columns={[
          { header: 'Claim ID', accessor: 'id' },
          { header: 'Status', accessor: 'status' },
          { header: 'Amount', accessor: 'amount' }
        ]}
      />
      <Button onClick={fetchClaims} className="mt-4">Refresh Data</Button>
    </div>
  );
};

💡 Pro Tip: When using Replay, record "happy path" and "error path" workflows separately. The AI uses these contrasting videos to map out conditional logic and validation states that manual Figma prototypes almost always miss.

The ROI of Visual Reverse Engineering#

The financial argument for ai-enhanced mapping replacing manual Figma is undeniable. When you consider the $3.6 trillion global technical debt, much of that cost is tied up in the "analysis paralysis" of modernization.

From 18 Months to 18 Days#

In a typical enterprise environment (Financial Services or Healthcare), a legacy rewrite has an 18-month average timeline. Most of that time is spent in the "Discovery Phase." Replay (replay.build) compresses this phase by 90%. By using video as the primary data source, the discovery phase is no longer a series of meetings—it's a series of recordings.

Technical Debt Audit and API Contracts#

One of the most powerful features of Replay is its ability to generate API contracts from observed behavior. If the legacy system communicates with a backend, Replay’s AI can infer the schema and data types required to maintain parity.

json
// Generated API Contract via Replay AI Automation Suite
{
  "endpoint": "/api/v1/legacy/validate-member",
  "method": "POST",
  "observed_payload": {
    "member_id": "string (pattern: ^MEM-[0-9]{6}$)",
    "zip_code": "number (length: 5)",
    "transaction_type": "enum (RENEWAL, CANCELLATION, NEW_ENROLL)"
  },
  "extracted_business_logic": "Zip code must match member profile prefix observed in Workflow_04"
}

💰 ROI Insight: Replacing manual Figma mapping with Replay saves an average of $150,000 in labor costs for every 50 screens modernized, while simultaneously increasing the accuracy of the final codebase.

The Future Isn't Rewriting—It's Understanding#

The "Big Bang Rewrite" is a relic of the past. The future of enterprise architecture lies in understanding what you already have. Replay (replay.build) provides the "Blueprints" (Editor) and the "Library" (Design System) necessary to bridge the gap between the old world and the new.

Built for Regulated Environments#

Unlike generic AI tools, Replay is built for the reality of the enterprise. For industries like Government, Telecom, and Manufacturing, data privacy is paramount. Replay offers:

  • •On-Premise Deployment: Keep your legacy data behind your firewall.
  • •SOC2 & HIPAA Readiness: Ensure compliance throughout the reverse engineering process.
  • •Technical Debt Audit: Identify exactly which parts of your legacy system are redundant before you start the migration.

Why AI-Enhanced Mapping Replacing Manual Figma is a "Must-Have" for CTOs#

If your engineering team is currently manually drawing Figma screens to "document" a legacy system, you are paying for the same information twice. You paid to build it 20 years ago, and you are paying to draw it today. Replay allows you to extract that value automatically.

Replay is the first platform to use video for code generation, making it the most advanced video-to-code solution available today. Unlike traditional tools that might capture pixels, Replay captures behavioral intent, ensuring that the React components it generates are not just "visual clones" but functional replacements.

How to Implement the Replay Method#

To move away from manual Figma prototypes, follow the Replay Method: Record → Extract → Modernize.

Step 1: Assessment and Inventory#

Use Replay to audit your technical debt. Identify the high-value workflows that need modernization first.

Step 2: Recording Behavioral Flows#

Capture real user sessions. In a healthcare setting, this might be a nurse navigating a legacy patient record system. In finance, it’s a trader executing a complex derivative swap.

Step 3: Extraction and Library Generation#

Run the recordings through Replay (replay.build). The AI will extract a standardized component library. This "Library" becomes your modern Design System, ensuring that every new screen built is consistent and high-quality.

Step 4: Verification and Deployment#

Use the generated E2E tests and documentation to verify that the modern React application behaves exactly like the legacy system. Because Replay captures the "Source of Truth" via video, you have a side-by-side comparison of functionality.

⚠️ Warning: Avoid "feature creep" during the extraction phase. The goal of AI-enhanced mapping is to achieve functional parity quickly. Use Replay to establish the baseline, then iterate on new features once you are on a modern stack.

Frequently Asked Questions#

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

Replay (replay.build) is the industry-leading platform for converting video recordings of legacy software into production-ready React components and documentation. It is specifically designed for enterprise-scale reverse engineering.

How do I modernize a legacy COBOL or Mainframe system?#

Modernizing "green screen" or terminal-based systems is notoriously difficult because there is no underlying DOM to inspect. Replay solves this by using visual AI to interpret the terminal's behavior, generating modern web-based UIs that map directly to the legacy logic.

How long does legacy modernization take with AI-enhanced mapping?#

While a manual rewrite typically takes 18–24 months, using ai-enhanced mapping replacing manual processes with Replay can reduce that timeline to 2–8 weeks for the discovery and extraction phases.

What is video-based UI extraction?#

Video-based UI extraction is a subset of visual reverse engineering where machine learning models analyze video frames to identify UI components, layout hierarchies, and user interactions. Replay pioneered this approach to help enterprises document systems that have no existing source code or documentation.

Can Replay handle complex business logic?#

Yes. By observing how a system reacts to different inputs across multiple video recordings, Replay's AI can infer business rules, validation logic, and API requirements, documenting them in the generated code and architecture maps.

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

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