Services · AI-built app rescue
Vibe code cleanup services: take your AI-built app from prototype to production
You built it fast with Lovable, Bolt, v0, Cursor or Claude Code, and it works, mostly. We find what will break in production, fix security and data access first, add the tests and deploy pipeline it never had, and leave you with a codebase engineers can keep building on.
Short answer
Vibe code cleanup is the work of turning an app generated with AI tools into production software: fixing access control and secrets, repairing payments and data logic, adding tests, monitoring and a deploy pipeline. Innovation Insight starts with a code audit ($3k to $8k, about one to two weeks) that ranks every issue by risk, then runs a stabilisation sprint ($6k to $18k, three to six weeks) on the critical fixes, with ongoing support from $1,500 a month.
Reviewed by Zain Khalid Malik, CTO & Co-founder · Updated
Why AI-built apps need a cleanup before they scale
AI app builders are very good at producing screens and flows that work in a demo. They are much less reliable at the parts nobody sees: who is allowed to read which rows, what happens when a payment webhook arrives twice, where the API keys live, and whether anything is tested. Veracode's GenAI Code Security Report (July 2025) found that AI-generated code introduced security vulnerabilities in 45 percent of its test cases. In May 2025, CVE-2025-48757 described Lovable-generated sites whose Supabase row level security let unauthenticated visitors read and write database tables. Lovable disputes it, saying each customer is responsible for their app's data. Neither means the tools are bad; it means a human engineer has to check the work before real users and real money arrive.
| What we usually find | Why it matters | Typical fix |
|---|---|---|
| Row level security missing or too permissive on Supabase or Firebase tables | Anyone with the public key can read or change other users' data | Write and test policies per table; move privileged work to server code |
| Secrets in the front end: service-role keys, Stripe secret keys, OpenAI keys | Keys can be copied from the browser and abused | Rotate keys; move calls behind server routes or edge functions |
| Payments that trust the browser or skip webhooks | Paid features unlock without payment, or customers are charged twice | Webhook-driven fulfilment with signature checks and idempotency |
| Business rules duplicated across components | Fixes in one place leave bugs in another | Move rules to one server-side module or database function |
| No tests, no staging, deploys from the builder | Every change risks breaking production | Tests on the critical paths, staging environment, CI/CD from Git |
| Hundreds of overlapping migrations and unused tables | Schema nobody understands; slow queries | Squash migrations, document the schema, add indexes |
| No logging or error tracking | You learn about failures from customers | Error tracking, structured logs and uptime alerts |
How a cleanup works
- Code audit ($3k to $8k, one to two weeks): we read the code and the database, run the app, test access control with two accounts, scan dependencies and secrets, and review payments and integrations. You get a written report that ranks every finding as critical, high, medium or low, with an estimate for each fix, and a recommendation: clean up, partly rebuild, or rebuild. The report is yours whatever you decide next.
- Stabilisation sprint ($6k to $18k, three to six weeks): critical and high findings first, usually access control, secrets and payments, then a staging environment, CI/CD, error tracking and tests on the flows that make money. Each fix is a reviewed pull request in your repository.
- Handover or continue: you keep building in Lovable or Cursor with guard rails in place, or we take over development with a documented codebase and a backlog.
- Ongoing support: monitoring, dependency updates and small changes from $1,500 a month on our maintenance and support plans.
Clean up or rebuild?
| Signal | Usually |
|---|---|
| The product is right and most screens work; problems are security, payments and missing tests | Clean up |
| Data model is wrong for where the product is going (for example single-user tables for a team product) | Partial rebuild of the data layer, keep the front end |
| Every fix breaks something else and nobody can explain the code | Rebuild the core with the same design, migrating data |
| You need features the builder cannot express, such as complex background jobs or native mobile | Move to a conventional stack for that part |
A full rebuild of a web MVP with us costs $15k to $40k; the audit tells you whether you need one before you spend that.
Work we have done on AI-built and inherited code
- An AI career-coaching SaaS generated in Lovable on Supabase (47 commits by the builder): in 54 follow-up commits our engineer fixed the Stripe payment and subscription flows, added subscription expiry logic, built the admin modules for reviewing applications and documents, and put the AI interview coach behind an admin-only feature flag.
- Paint Nite: not AI-built, but the same takeover discipline. The purchase flow lived in one function of about 1,200 lines with no Stripe idempotency keys; it became an idempotent checkout pipeline with 754 automated test files running on every pull request.
- Chat Your History and Edge OCR: signature-verified Stripe webhooks, subscription state kept in sync from webhooks, and RBAC with every mutation authorised and logged, the patterns a cleanup usually adds.
What to send us
- Read access to the repository (GitHub export from Lovable, Bolt or v0 works) and, if possible, a read-only database user.
- A list of the user roles and what each should be able to see and do.
- The third-party services the app uses: Supabase or Firebase, Stripe, email, AI providers.
- What is going wrong now, and what is coming next (a launch date, an investor demo, an enterprise customer's security questionnaire).
We sign an NDA before access if you need one, use read-only credentials during the audit, and follow the AI tool rules in how we use Claude Code on client projects. For a deeper takeover checklist see how to take over an existing codebase.
Sources and further reading
Next step
Tell us what you're building and get a written estimate.
A senior engineer replies within one business day. NDA on request.
Products we've shipped, and what happened next.
Case studies written from the technical documentation of each project: the stack, the scale and the outcome.
Questions we get asked a lot.
What is vibe code cleanup?
Fixing an app generated with AI tools such as Lovable, Bolt, v0 or Cursor so it is safe and maintainable in production: access control, secrets, payments, data model, tests, monitoring and deployment.
How much does a vibe code cleanup cost?
A code audit costs $3k to $8k and takes one to two weeks. Fixing the critical findings in a stabilisation sprint usually costs $6k to $18k over three to six weeks. Ongoing support starts from $1,500 a month.
Is my Lovable or Bolt app secure?
It may be, but check: the most common problem is missing or permissive row level security on Supabase tables, followed by secret keys in the browser. Our audit tests both with real accounts.
Do I have to stop using the AI builder?
No. Many clients keep using it for UI work. We move security-critical logic to server code and database policies, and add tests so a generated change that breaks something fails before it ships.
Should I clean up or rebuild?
Clean up when the product is right and the problems are security, payments and tests. Rebuild parts when the data model is wrong for where the product is going. The audit report makes that recommendation with costs for each path.