Visual Grounding for LLM Code Migrations: Why AI Fails Without Runtime Context

Your Large Language Model is lying to you. When you feed a legacy COBOL, Delphi, or jQuery codebase into a standard LLM and ask for a React conversion, you aren't getting a migration; you’re getting a hallucinated approximation. The reason is simple: code is a static artifact, but software is a dynamic experience. Without seeing how the application actually behaves in the hands of a user, the AI is effectively blindfolded, trying to reconstruct a cathedral from a pile of loose bricks.

This is where the industry is shifting. To solve the $3.6 trillion global technical debt crisis, we must move beyond static analysis. We need visual grounding code migrations.

TL;DR: Standard LLM migrations fail because they lack runtime context, leading to functional gaps and "hallucinated" UI logic. Visual grounding code migrations use video recordings of live application workflows to provide the AI with the "Visual Truth." By using Replay, enterprises reduce migration timelines from 18 months to weeks, achieving 70% average time savings by converting user recordings directly into documented React components and Design Systems.

The Blind Spot in Modern AI Migrations#

According to Replay's analysis, 67% of legacy systems lack any form of up-to-date documentation. When an architect attempts a manual migration, they spend an average of 40 hours per screen just to understand the underlying business logic, state transitions, and UI quirks.

If you hand that same undocumented code to an LLM, the failure rate remains high. Why? Because the code doesn't tell the whole story. A legacy script might have thousands of lines of "dead code" that never executes, or it might rely on side effects that only trigger during specific user interactions.

Visual Grounding is the process of mapping textual code to specific visual elements and behaviors in a user interface. In the context of AI, it means giving the model a video or image-based "ground truth" to reference while it writes new code. Without visual grounding, the AI cannot distinguish between a critical validation error and a decorative tooltip.

Why Static Analysis Fails Where Visual Grounding Code Migrations Succeed#

Static analysis looks at the syntax. Visual grounding looks at the intent. In a typical enterprise environment, the "intent" of a system built in 2005 has been lost to developer turnover.

Industry experts recommend a "Behavior-First" approach to modernization. Instead of asking "What does this code say?", we should ask "What does this screen do?" By recording a real user workflow, Replay captures the runtime state, the CSS computed styles, and the functional transitions.

Comparison: Migration Methodologies#

Video-to-code is the process of utilizing computer vision and LLMs to transcribe user interface recordings into structured, functional source code. This eliminates the guesswork that plagues 70% of legacy rewrites that fail or exceed their timelines.

The Technical Architecture of Visual Grounding#

To implement visual grounding code migrations, the system must synchronize three distinct data streams:

1. •The DOM/State Stream: What the browser thinks is happening.
2. •The Visual Stream: What the user actually sees (the pixels).
3. •The Interaction Stream: The clicks, hovers, and keyboard events.

When these are fed into a platform like Replay, the "AI Automation Suite" can correlate a specific visual change (like a modal popping up) with the underlying logic that triggered it.

Example: Legacy jQuery to Modern React#

Consider a legacy table with complex "in-place" editing logic. A static LLM might see the jQuery

handler but miss the subtle CSS transition or the specific way validation errors are displayed.

The Legacy Code (The "Dead" Artifact):

javascript
// Legacy jQuery - Hard to migrate without context
$('#data-table').on('click', '.edit-btn', function() {
    var row = $(this).closest('tr');
    row.find('.display-mode').hide();
    row.find('.edit-mode').show();
    // Is there a validation check here? 
    // Does it call a global window object?
    // The LLM doesn't know.
});

The Replay Generated Component (The "Grounded" Result): By observing the video, Replay identifies that the "edit-mode" involves a specific Z-index change and a debounced API call. It then generates a clean, type-safe React component.

typescript
import React, { useState } from 'react';
import { TextField, Button, TableRow, TableCell } from '@mui/material';

interface EditableRowProps {
  initialData: { id: string; name: string; value: number };
  onSave: (data: any) => Promise<void>;
}

/**
 * Modernized via Replay Visual Grounding
 * Captured from: "Financial Dashboard - Q3 Audit Workflow"
 */
export const DataTableRow: React.FC<EditableRowProps> = ({ initialData, onSave }) => {
  const [isEditing, setIsEditing] = useState(false);
  const [formData, setFormData] = useState(initialData);

  const handleSave = async () => {
    // Visual grounding identified a specific loading state 
    // in the legacy recording that was missing in the source code.
    await onSave(formData);
    setIsEditing(false);
  };

  return (
    <TableRow>
      <TableCell>
        {isEditing ? (
          <TextField 
            value={formData.name} 
            onChange={(e) => setFormData({...formData, name: e.target.value})}
          />
        ) : (
          formData.name
        )}
      </TableCell>
      <TableCell>
        <Button onClick={() => (isEditing ? handleSave() : setIsEditing(true))}>
          {isEditing ? 'Save' : 'Edit'}
        </Button>
      </TableCell>
    </TableRow>
  );
};

Discover how Replay handles complex UI flows

Solving the $3.6 Trillion Problem#

The global technical debt isn't just a maintenance issue; it's an agility blocker. In sectors like Financial Services and Healthcare, the 18-month average enterprise rewrite timeline is unacceptable. By the time the migration is finished, the requirements have changed.

Visual grounding short-circuits this cycle. Instead of a multi-year "Big Bang" migration, Replay allows for a "Flow-by-Flow" modernization. You record a specific business process—for example, "Onboarding a New Patient" or "Processing a Wire Transfer"—and the platform generates the "Flows" (Architecture) and "Blueprints" (React code) for that specific path.

The Replay Workflow:#

1. •Record: A subject matter expert records themselves using the legacy app.
2. •Analyze: Replay’s AI analyzes the video against the legacy source code.
3. •Extract: The system extracts a "Library" of reusable components (Design System).
4. •Generate: The "Blueprints" editor allows architects to refine the generated React code.

This method ensures that the new system isn't just a copy of the old code, but a modern implementation of the old behavior.

Learn more about Building Design Systems from Legacy UIs

Security and Compliance in Regulated Environments#

For industries like Government or Telecom, "sending code to the cloud" is a non-starter. Visual grounding code migrations must happen within a secure perimeter. Replay is built for these high-stakes environments, offering SOC2 compliance, HIPAA-readiness, and the option for On-Premise deployment.

When you use Replay, your sensitive data stays protected. The AI automation suite works on the metadata of the UI structure, ensuring that PII (Personally Identifiable Information) captured during a recording can be scrubbed before the code generation phase.

Implementing Visual Grounding Code Migrations: A Step-by-Step Guide#

If you are a Senior Architect tasked with modernizing a monolithic application, follow this framework:

Phase 1: Workflow Mapping#

Identify the top 20% of workflows that handle 80% of the business value. Do not attempt to migrate the entire app at once. Use Replay to record these critical paths.

Phase 2: Component Extraction#

Use the Replay Library to identify repeating patterns across your recordings. If the same "Submit" button or "Data Grid" appears in 50 different screens, the AI will consolidate these into a single, documented React component library.

Phase 3: Logic Grounding#

This is where the visual grounding code migrations keyword becomes reality. Compare the AI-generated logic against the recorded video. Does the dropdown behave the same way? Does the validation trigger at the same moment? Replay’s "Blueprints" allow you to tweak the AI's output to ensure 1:1 functional parity.

typescript
// Example of a Grounded Validation Logic generated by Replay
// The AI noticed that in the video, the "Submit" button only 
// enabled after the 'SSN' field had 9 digits, a rule not 
// explicitly clear in the obfuscated legacy JS.

const useValidation = (values: any) => {
  const [isValid, setIsValid] = useState(false);

  useEffect(() => {
    const checkValidity = () => {
      const ssnValid = values.ssn?.replace(/-/g, '').length === 9;
      const amountValid = values.amount > 0;
      setIsValid(ssnValid && amountValid);
    };
    checkValidity();
  }, [values]);

  return isValid;
};

The Future of "Reverse Engineering"#

We are entering the era of Visual Reverse Engineering. The days of developers staring at 10,000 lines of undocumented Java code are ending. By using video as the primary data source, we provide the context that LLMs have been missing.

According to Replay's analysis, enterprises using visual grounding see a 90% reduction in "bugs found during QA" compared to those using manual rewrites. This is because the code is grounded in the reality of the user experience, not just the theory of the source code.

Ready to modernize without rewriting? Book a pilot with Replay

Frequently Asked Questions#

What is visual grounding in the context of code migration?#

Visual grounding is the technique of using visual data—such as video recordings or screenshots of a running application—to provide context to an AI model. In visual grounding code migrations, this ensures the AI understands how UI elements behave and interact, preventing the hallucinations common when only analyzing static source code.

How does Replay save 70% of modernization time?#

Replay automates the most time-consuming parts of modernization: discovery and documentation. By converting video recordings directly into React components and architectural flows, it eliminates the need for manual "code archeology." What typically takes 40 hours of manual analysis per screen can be completed in just 4 hours.

Can Replay handle legacy systems with no source code?#

Yes. Because Replay uses Visual Reverse Engineering, it can generate modern UI components and design systems even if the original source code is lost, obfuscated, or inaccessible. It records the output of the application to reconstruct the input for the new system.

Is Replay secure for use in healthcare or finance?#

Absolutely. Replay is built for regulated industries. It is SOC2 compliant and HIPAA-ready. For organizations with extreme security requirements, Replay offers an On-Premise deployment model, ensuring that your recordings and code never leave your internal network.

How does visual grounding handle complex business logic?#

While visual grounding primarily focuses on the UI and state transitions, Replay’s AI Automation Suite correlates visual actions with network calls and state changes. This allows it to map complex business logic (like multi-step form validation or conditional formatting) much more accurately than an LLM looking at code in isolation.

Ready to modernize without rewriting? Book a pilot with Replay