AI Code Cleanup

AI Code CleanupAI Wrote It. Humans Clean It.

AI coding tools generate working code fast. But the code is often messy, inconsistent, and bloated. Our AI Code Cleanup service takes your AI-generated code and makes it clean, efficient, and maintainable — without rewriting from scratch.

What We Clean

Eight cleanup services to transform your AI-generated code into production-quality software.

Remove Duplicate Code

Find and eliminate duplicated logic, components, and utilities

Refactor Bad Architecture

Restructure messy components into clean, maintainable modules

Fix Inconsistent Patterns

Standardize naming, formatting, and coding patterns across the codebase

Reduce Dependencies

Remove unnecessary packages, replace bloated libraries with lighter alternatives

Improve Performance

Optimize rendering, reduce bundle size, fix slow queries

Add Tests

Write unit and integration tests for critical code paths

Improve Documentation

Add code comments, README files, and API documentation

Fix Security Issues

Address exposed secrets, auth gaps, and vulnerability patterns

Before & After

Before Cleanup

  • Duplicated code across 12 files
  • Inconsistent naming
  • 0 tests
  • No documentation
  • Unused dependencies
  • Security gaps

After Cleanup

  • DRY codebase
  • Consistent patterns
  • 80%+ test coverage
  • Documented APIs
  • Minimal dependencies
  • Security reviewed

Fixed-Price Packages

No hidden costs. No hourly billing. Pick a package and we deliver.

Quick Cleanup

AED 5,000
$1,359 · 3-5 days
  • Deduplicate code
  • Standardize patterns
  • Basic documentation
Get Started
Most Popular

Standard Cleanup

AED 10,999
$4,099 · 1-2 weeks
  • Full cleanup + refactoring
  • Test coverage
  • Comprehensive documentation
Get Started

Deep Cleanup

AED 12,999
$8,199 · 2-4 weeks
  • Complete codebase overhaul
  • Architecture improvement
  • Comprehensive testing
Get Started

Our Process

1

We Review

Quick scan of your AI-generated codebase to identify cleanup priorities

2

We Plan

Fixed-scope cleanup plan with clear deliverables and timeline

3

We Clean

Systematic cleanup following your cleanup package scope

4

We Deliver

Clean, documented, tested code with a summary of all changes

Get a Cleanup Quote

Tell us about your AI-generated codebase and we'll recommend the right cleanup package.

Get Your Free Consultation

Share your details and we'll get back to you shortly.

Free Strategy Plan
NDAs Signed
Expert Advice
FAQ

Frequently Asked Questions

A productized service to clean AI-generated code without a full rewrite. We take your AI-generated codebase and make it clean, efficient, and maintainable.

Cleanup focuses on code quality. Rescue includes security, architecture, deployment, and more. Cleanup is cheaper and faster — ideal when the code works but needs polish.

No — we clean and improve existing code. A rewrite is only recommended when cleanup isn't sufficient due to fundamental architectural issues.

We clean code generated by Lovable, Bolt, Replit, Cursor, Claude Code, Copilot, and any other AI-powered coding tool.

Quick Cleanup: 3-5 days, Standard Cleanup: 1-2 weeks, Deep Cleanup: 2-4 weeks depending on codebase size and complexity.

Yes — many clients start with cleanup, then add security hardening or production engineering as next steps.

What Usually Breaks, Tool by Tool

Each AI builder has its own habits. Knowing them tells us where to look first, which is why most audits find the serious problems on day one.

Lovable app rescue

React + Supabase

Lovable development

What we find

Supabase tables with Row Level Security turned off or set too loosely, so the public key in the browser can read or change other users' data. A 2025 vulnerability report (CVE-2025-48757) found this pattern on many Lovable-built sites.

What we do

We write RLS policies table by table, move sensitive logic into edge functions, and test access as a logged-out user and as a second account.

Bolt app rescue

Vite / Next.js, often Supabase

Bolt development

What we find

Secret keys stored in client-side environment variables (anything prefixed VITE_ ends up in the browser bundle), and long fix-it prompt loops that leave duplicate components and dead code behind.

What we do

We move secrets to the server, rotate the exposed ones, and remove the duplicated code so the next change does not break three other screens.

Replit app rescue

Replit Agent + Postgres

Replit development

What we find

One database shared by development and production, so an agent's test run or migration touches live data. In July 2025 a Replit agent deleted a founder's production database during a code freeze, which made this risk widely known.

What we do

We separate development and production databases, add automated backups with a tested restore, and limit what an agent can run against production.

Cursor, Claude Code & Codex app rescue

Your own repo, any stack

Cursor development

What we find

Large AI-written changes merged without review: the same logic written three different ways, dependencies nobody chose on purpose, and no tests to show what an edit broke.

What we do

We add tests around the main user flows, remove unused dependencies, merge the duplicated logic and set up pull-request checks before anything reaches production.

v0 app rescue

Next.js

What we find

Server actions and API routes generated without an authentication or ownership check, so anyone who finds the endpoint can call it.

What we do

We add session and ownership checks to every server action and route, plus input validation and rate limits on public endpoints.

Already seeing these problems? Our vibe-coded app rescue fixes them in 2-4 weeks, or start with a vibe-coded app audit.

Rescue or Rebuild? How We Decide

Not every AI-built app is worth saving. We tell you which side yours falls on after the audit, before you pay for fixes.

Rescue makes sense when

  • The main user flows work, they are just fragile
  • Data sits in a real database with sensible tables
  • The stack is mainstream (React, Next.js, Supabase, Firebase, Postgres)
  • Problems are concentrated in auth, security, payments or performance

A rebuild is cheaper when

  • Login, payments or permissions only exist in the frontend
  • Data is stored in local storage, JSON files or one giant table
  • Every fix breaks something unrelated, even after cleanup
  • The app has to meet a compliance standard the current design cannot reach

Worth saving? See vibe-coded app rescue. Better to rebuild? A rebuild keeps your designs, copy and lessons from the first version, so it is usually much faster than the original build. See prototype to product.

Get in Touch

Tell us about your project

  • We respond within 12 hours
  • NDA available on request
  • Dedicated consultant specialists

WhatsApp Us

+971 54 483 2290

Direct Email

[email protected]
Sourced & Verified

Sourced Context on AI Development

Sourced context, grounded in verifiable references.

Artificial intelligence systems learn from data to perform tasks — such as language understanding, image recognition and decision support — that typically require human intelligence.[1]

Generative large language models can draft text, answer questions and automate routine conversations, making them widely used for customer support and content production.[2]

Sources & References

  1. [1]Artificial intelligence — Wikipedia · en.wikipedia.org/wiki/Artificial_intelligence
  2. [2]Large language model — Wikipedia · en.wikipedia.org/wiki/Large_language_model