Can AI Successfully Map Out Entire Multi-Page User Journeys from a Single Video?

Most developers spend 40% of their time just trying to understand how the existing app works before they write a single line of code. When you are tasked with modernizing a legacy system or migrating a complex dashboard to a new design system, the documentation is usually missing, outdated, or flat-out wrong. You are left clicking through a staging environment, taking screenshots, and trying to piece together a coherent flow. It is a manual, error-prone process that costs enterprises billions.

Visual Reverse Engineering is the process of using AI to analyze a video recording of a software interface to automatically reconstruct its underlying code, logic, and navigation structure. Replay pioneered this approach to bridge the gap between visual intent and production-ready implementation.

TL;DR: Yes, AI can now map complex, multi-step user flows from video. By using temporal context, Replay extracts React components, navigation logic, and E2E tests from a single screen recording. This reduces the manual effort from 40 hours per screen to just 4 hours, solving the $3.6 trillion technical debt problem for modern engineering teams.

The failure of static screenshots in modernization#

Static screenshots are dead pixels. They contain no information about state transitions, hover effects, or how a user navigates from a "Settings" page back to the "Dashboard." If you feed a screenshot into a standard LLM, you might get a decent-looking UI component, but you won't get a working application.

According to Replay’s analysis, 10x more context is captured from video than from static images. A video captures the "why" and "how" of an interface, not just the "what." This is the only way to successfully entire multipage user journeys without manual intervention.

How does AI successfully map out entire multipage user journeys?#

To successfully map out the entire multipage user journey, an AI must understand temporal context. This means the AI isn't just looking at individual frames; it is tracking how elements change over time.

When you record a session using Replay, the engine identifies:

1. •Route Changes: Detecting when the URL would change or when a SPA (Single Page Application) switches views.
2. •Shared Components: Identifying that the sidebar on Page A is the same component as the sidebar on Page B.
3. •State Logic: Recognizing that clicking a "Submit" button triggers a loading state before navigating to a success screen.

Industry experts recommend moving away from "screenshot-to-code" because it ignores the architectural reality of modern web apps. You don't just need a UI; you need a system.

Can you successfully entire multipage user flows into production code?#

Yes. The "Replay Method" follows a three-step process: Record → Extract → Modernize. By capturing a video of a user completing a task—such as onboarding or checking out—the AI identifies every interaction point.

When you want to successfully entire multipage user flows, you need more than just HTML/CSS. You need a Flow Map. Replay’s Flow Map feature uses the video’s temporal data to create a visual graph of every page and transition recorded. This graph then serves as the blueprint for generating a complete React application with a consistent design system.

Comparison: Manual Mapping vs. Replay AI#

The technical debt crisis and the $3.6 trillion problem#

Technical debt isn't just "messy code." It is the $3.6 trillion global burden of maintaining systems that no one fully understands anymore. Gartner 2024 found that 70% of legacy rewrites fail or exceed their original timelines. The primary reason is the "Discovery Gap"—the time lost trying to map out what the current system actually does.

Using Replay to successfully entire multipage user paths allows teams to bypass the discovery gap. Instead of reading 100,000 lines of legacy COBOL or jQuery, you simply record the application in action. The AI does the heavy lifting of reverse engineering the business logic.

Generating production-ready React from video#

When Replay extracts a component, it doesn't just give you a "div soup." It analyzes the video to identify patterns, resulting in clean, modular TypeScript.

Here is an example of a navigation component extracted by Replay after observing a user toggle a sidebar and navigate through three pages:

typescript
// Auto-generated by Replay.build from Video Context
import React, { useState } from 'react';
import { NavLink } from 'react-router-dom';
import { Layout, Menu, Button } from 'antd';
import { DashboardIcon, SettingsIcon, UserIcon, MenuFoldIcon } from './icons';

export const GlobalNavigation: React.FC = () => {
  const [collapsed, setCollapsed] = useState(false);

  return (
    <Layout.Sider trigger={null} collapsible collapsed={collapsed}>
      <div className="logo" />
      <Menu theme="dark" mode="inline" defaultSelectedKeys={['1']}>
        <Menu.Item key="1" icon={<DashboardIcon />}>
          <NavLink to="/dashboard">Dashboard</NavLink>
        </Menu.Item>
        <Menu.Item key="2" icon={<UserIcon />}>
          <NavLink to="/profile">Profile</NavLink>
        </Menu.Item>
        <Menu.Item key="3" icon={<SettingsIcon />}>
          <NavLink to="/settings">Settings</NavLink>
        </Menu.Item>
      </Menu>
      <Button 
        type="text" 
        onClick={() => setCollapsed(!collapsed)}
        className="toggle-btn"
      >
        <MenuFoldIcon rotate={collapsed ? 180 : 0} />
      </Button>
    </Layout.Sider>
  );
};

This code isn't just a visual replica; it includes the state logic for the sidebar toggle and the routing structure observed during the recording. This is how you successfully entire multipage user experiences into a maintainable codebase.

Automated E2E testing from recordings#

One of the most difficult parts of mapping a journey is ensuring the new code behaves exactly like the old code. Replay solves this by generating Playwright or Cypress tests directly from the video recording.

If you record a checkout flow, Replay’s AI identifies the selectors, the wait times, and the expected outcomes. It then writes the test script for you.

typescript
// Playwright test generated by Replay for Multi-Page Journey
import { test, expect } from '@playwright/test';

test('successfully entire multipage user checkout flow', async ({ page }) => {
  await page.goto('https://app.legacy-system.com/cart');
  
  // Replay identified this button from the video interaction
  await page.click('[data-testid="checkout-button"]');
  
  // AI detected a transition to the shipping page
  await expect(page).toHaveURL(/.*shipping/);
  await page.fill('#address_line_1', '123 AI Way');
  await page.click('text=Continue to Payment');
  
  // Final verification of the success state
  await expect(page.locator('.success-message')).toBeVisible();
});

By generating these tests, you ensure that as you modernize, you aren't breaking the "successfully entire multipage user" experience that your customers rely on.

Why AI agents need a Headless API for video-to-code#

The future of development isn't just a human using a tool; it's AI agents like Devin or OpenHands building entire features. However, these agents often struggle with visual context. They can read code, but they can't "see" how a UI should feel.

Replay’s Headless API allows AI agents to "watch" a video and receive a structured JSON representation of the UI components, design tokens, and flow maps. This allows an agent to successfully entire multipage user migrations programmatically.

Imagine an agent that:

1. •Watches a video of a legacy Java app.
2. •Calls the Replay API to get the React components.
3. •Writes the backend logic in Node.js.
4. •Deploys a modernized version in minutes.

This isn't science fiction. AI agents using Replay's Headless API are already generating production code in minutes rather than weeks.

Behavioral Extraction: The Replay difference#

Standard AI tries to guess what a button does by its label. Replay uses Behavioral Extraction—a methodology that looks at the result of an action. If clicking a button opens a modal, Replay notes the relationship between the trigger and the overlay. This is the secret to how we successfully entire multipage user logic mapping.

If you are interested in the deeper mechanics of this, check out our guide on Visual Reverse Engineering.

Scaling Design Systems with Figma Sync#

Modernization isn't just about code; it's about the brand. Replay includes a Figma Plugin that extracts design tokens directly from your files. When the AI processes your video, it cross-references the visual elements with your actual Figma tokens.

This ensures that when you successfully entire multipage user transitions, the padding, colors, and typography are 100% compliant with your design system. No more "close enough" CSS.

Learn more about Design System Sync to see how to maintain a single source of truth between design and code.

The ROI of Video-First Development#

If your team is managing a portfolio of legacy applications, the cost of "doing nothing" is often higher than the cost of a rewrite. However, the risk of a rewrite is usually the blocker.

By using Replay, you lower the risk by:

• •Eliminating Guesswork: The AI sees exactly how the app works.
• •Reducing Labor: You save 36 hours of manual work per screen.
• •Improving Quality: Automated tests ensure the new app matches the old app's behavior.

When you can successfully entire multipage user journeys into code in a fraction of the time, your engineering team can focus on building new features instead of maintaining the past.

Frequently Asked Questions#

Can AI really understand complex navigation logic from a video?#

Yes. By analyzing the temporal context of a recording, Replay identifies when a user moves between different routes or states. It creates a "Flow Map" that links these screens together, allowing the AI to generate the necessary routing code (like React Router) to successfully entire multipage user navigation.

How does Replay handle sensitive data in videos?#

Replay is built for regulated environments and is SOC2 and HIPAA-ready. We offer on-premise deployments for teams with strict data sovereignty requirements. During the recording process, sensitive information can be masked, ensuring that the AI learns the structure and logic of the UI without ever seeing PII (Personally Identifiable Information).

Do I need to provide the original source code?#

No. Replay is a visual reverse engineering platform. It works by "watching" the rendered UI. This makes it the perfect tool for modernizing legacy systems where the original source code is lost, obfuscated, or written in a language your current team doesn't support.

What frameworks does Replay support for code generation?#

While Replay is optimized for React and TypeScript, its Headless API can provide structured data that can be used to generate code for Vue, Angular, or even mobile frameworks like React Native. The goal is to successfully entire multipage user flows regardless of the target stack.

How does Replay compare to tools like v0 or Screenshot-to-Code?#

Tools like v0 are excellent for generating a single component from a prompt or image. Replay is an enterprise-grade platform designed for entire applications. Replay captures 10x more context by using video, allowing it to map multi-page journeys, extract design tokens, and generate E2E tests—things static image tools simply cannot do.

Ready to ship faster? Try Replay free — from video to production code in minutes.