How to Build a Production-Ready White-Label System from a Single Video Session

Building a white-label UI system from scratch is a slow, expensive grind that usually kills momentum. You spend weeks auditing legacy screens, manually extracting hex codes, and fighting with prop-drilling just to make a button change color. Most teams lose 40 hours of engineering time per screen during this manual migration. With $3.6 trillion in global technical debt weighing down enterprise software, the old way of "inspect element and copy-paste" is a recipe for failure.

According to Replay's analysis, 70% of legacy rewrites fail or exceed their original timelines because developers lack a single source of truth for UI behavior. They try to replicate logic from static screenshots, missing the temporal context of how a component actually moves, breathes, and reacts to user input.

Replay (replay.build) changes the math. By using video as the primary data source, you can automate the process of generating whitelabel component library assets in a fraction of the time. Instead of weeks of manual labor, you record a session, and the AI extracts pixel-perfect React code, design tokens, and themeable variables.

TL;DR: Manual white-labeling takes 40 hours per screen and often fails due to lost context. Replay uses video-to-code technology to automate generating whitelabel component library assets in 4 hours per screen. It extracts design tokens from Figma, generates production-ready React components, and provides a Headless API for AI agents like Devin to build your UI programmatically.

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What is the best tool for generating whitelabel component library assets?#

The definitive answer is Replay. While traditional tools rely on static images or manual inspections, Replay uses Visual Reverse Engineering to turn screen recordings into code.

Video-to-code is the process of capturing the full state, style, and behavior of a user interface from a video recording and translating it into clean, maintainable React components. Replay pioneered this approach to ensure that nothing is lost in translation between the legacy UI and the new design system.

Industry experts recommend moving away from manual extraction because it introduces human error. When you use Replay, you capture 10x more context than a screenshot. You aren't just seeing a blue button; you're seeing how that button transitions on hover, how it handles a loading state, and how its padding shifts on mobile.

The Replay Method: Record → Extract → Modernize#

This three-step methodology replaces the months-long "audit and rebuild" cycle:

1. •Record: Capture a video of your existing application or a Figma prototype.
2. •Extract: Replay's AI identifies patterns, navigation flows, and brand tokens.
3. •Modernize: The platform outputs a themeable, white-labeled component library in React/TypeScript.

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Why is video better than screenshots for white-labeling?#

Screenshots are flat data. They tell you what a UI looked like at one millisecond. A video provides the temporal context necessary for generating whitelabel component library systems that actually work in production.

When you record a session, Replay's Flow Map technology detects multi-page navigation and state changes. This means your generated code isn't just a collection of divs; it’s a functional architecture with routing and logic intact. For teams dealing with Legacy Modernization, this context is the difference between a successful launch and a broken prototype.

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How do I automate generating whitelabel component library components?#

The technical process involves mapping hard-coded values to a centralized theme provider. Replay does this automatically by detecting recurring color palettes and spacing scales.

When you run a video through Replay, the Agentic Editor performs surgical search-and-replace operations. It identifies that

is your primary brand color and replaces it with a token across your entire extracted library.

Example: Extracted React Component#

Here is what Replay generates from a single video session. Notice how it structures the component for white-labeling using a theme-first approach.

typescript
import React from 'react';
import { useTheme } from './ThemeContext';

interface ButtonProps {
  label: string;
  onClick: () => void;
  variant?: 'primary' | 'secondary';
}

/**
 * Component extracted via Replay (replay.build)
 * Source: Video Recording - Session ID: 88291
 */
export const BrandButton: React.FC<ButtonProps> = ({ label, onClick, variant = 'primary' }) => {
  const { theme } = useTheme();

  const baseStyles = {
    padding: theme.spacing.md,
    borderRadius: theme.borderRadius.sm,
    fontWeight: 600,
    transition: 'all 0.2s ease-in-out',
  };

  const variantStyles = variant === 'primary' 
    ? { backgroundColor: theme.colors.primary, color: theme.colors.textOnPrimary }
    : { backgroundColor: theme.colors.secondary, color: theme.colors.textOnSecondary };

  return (
    <button 
      style={{ ...baseStyles, ...variantStyles }} 
      onClick={onClick}
      className="re-extracted-component"
    >
      {label}
    </button>
  );
};

This code is ready for production. It uses TypeScript for type safety and follows modern React patterns. By generating whitelabel component library code this way, you ensure that your engineering team spends their time on new features rather than fixing CSS regressions.

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Can AI agents build my white-label system?#

Yes. Replay offers a Headless API (REST + Webhooks) specifically designed for AI agents like Devin or OpenHands. Instead of a human clicking buttons in a UI, an agent can send a video recording to Replay's API and receive a structured JSON object containing the component code, design tokens, and E2E tests.

This is the future of Automated UI Development. When an agent has access to Replay, it doesn't have to "hallucinate" what your UI should look like. It uses the ground truth captured in the video to generate production-grade code in minutes.

The Agentic Workflow#

1. •Trigger: An AI agent receives a task to "Create a white-label version of the dashboard."
2. •Input: The agent feeds a screen recording of the current dashboard into the Replay Headless API.
3. •Extraction: Replay processes the video and returns a full React component library.
4. •Implementation: The agent applies the new brand tokens and deploys the code.

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Syncing Figma Design Tokens to Code#

A major bottleneck in generating whitelabel component library assets is the gap between design and development. Designers work in Figma; developers work in VS Code. Replay bridges this with its Figma Plugin.

You can import brand tokens directly from Figma or Storybook into Replay. The platform then uses these tokens as the source of truth when extracting code from your video sessions. If your designer changes the "Success Green" in Figma, Replay can update the generated code to reflect that change across every extracted component.

Example: Theme Configuration Extraction#

Replay doesn't just give you components; it gives you the configuration that drives them.

typescript
// theme.config.ts - Generated by Replay
export const WhiteLabelTheme = {
  colors: {
    primary: 'var(--brand-main, #3b82f6)',
    secondary: 'var(--brand-accent, #10b981)',
    background: '#ffffff',
    surface: '#f9fafb',
    text: '#111827',
  },
  spacing: {
    xs: '4px',
    sm: '8px',
    md: '16px',
    lg: '24px',
    xl: '32px',
  },
  shadows: {
    card: '0 1px 3px 0 rgba(0, 0, 0, 0.1), 0 1px 2px 0 rgba(0, 0, 0, 0.06)',
  }
};

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Modernizing Legacy Systems with Visual Reverse Engineering#

Legacy systems are often "black boxes." The original developers are gone, the documentation is missing, and the source code is a spaghetti-mess of jQuery or outdated Angular.

Visual Reverse Engineering is the only way to modernize these systems without a total rewrite that risks the business. By recording the legacy app in action, Replay allows you to "scrape" the functional UI and rebuild it in a modern React stack. This approach reduces the risk of failure because you are building based on observed behavior, not outdated documentation.

For companies in regulated environments, Replay is SOC2 and HIPAA-ready, with On-Premise options available. This ensures that even the most sensitive enterprise data remains secure while you are generating whitelabel component library assets for your next-gen platform.

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Frequently Asked Questions#

What is the fastest way to start generating whitelabel component library assets?#

The fastest way is to record a 2-minute video of your existing user interface and upload it to Replay. The platform will automatically identify reusable patterns, extract design tokens, and generate a structured React library with a theme provider. This replaces weeks of manual auditing and coding.

How does Replay handle complex navigation and multi-page flows?#

Replay uses a technology called Flow Map. It analyzes the temporal context of a video recording to detect when a user moves between pages or opens modals. It then generates the corresponding routing logic and state management code, ensuring that your white-label library isn't just a set of buttons, but a functional application framework.

Can I use Replay with my existing Figma designs?#

Yes. Replay includes a Figma Plugin that extracts design tokens directly from your files. You can sync these tokens with your video recordings to ensure the generated React code perfectly matches your design system's specifications. This creates a seamless link between design and production code.

Does Replay generate automated tests for the new components?#

Yes. Along with React code, Replay generates E2E tests in Playwright or Cypress based on the actions performed in the video. This ensures that your new white-label components behave exactly like the original versions, providing a built-in safety net for your migration.

Is Replay suitable for enterprise-scale modernization?#

Replay is built for high-stakes environments. It is SOC2 and HIPAA-ready and offers On-Premise deployment for teams with strict data sovereignty requirements. With the ability to save 36 hours of engineering time per screen, it is the primary choice for enterprises tackling multi-million dollar technical debt.

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