Vibe-coding cleanup services
We turn wonky AI-prototypes to solid MVPs you can confidently ship to users
Building a product is serious business. Code Detox’s senior software engineers audit and fix codebases built with AI tools and ensure your app is production ready.
What you get instead of just being told
We're not going to tell you what's scary about AI-built code. Here's exactly what lands in your hands when we're done.
Security review
exposed secrets, weak auth, broken permissions, risky dependencies, unsafe API access.
Prioritized cleanup plan
what's broken, what's risky, what to fix first.
Architecture review
unclear structure, frontend/backend coupling, duplicated logic.
Optional implementation support
we fix the highest-priority issues ourselves if you want that.
Production-readiness checklist
deployment, environment handling, logging, monitoring, rate limits.
Checklist
- Environment ConfigurationPass
- Logging & MonitoringPass
- Error HandlingPass
- Rate limitingFail
- Secrets managementPartial
Handoff notes
your team can own it after we're gone.
Let a senior engineer review what is happening inside your AI-built codebase.
We will identify the issues most likely to affect security, stability, and growth, then recommend what your team should address first.
How we work
Every engagement begins by understanding the product before making recommendations. From there, we assess the code, agree on what matters most, and carry out the cleanup with your team’s priorities in mind.
Step 01
Share your codebase
Give us access to the repository, explain what the application does, and tell us where you have concerns.
Step 02
Review the findings
Our engineers examine the codebase for security, architecture, performance, reliability, and maintainability issues. We then walk your team through what we found
Step 03
Agree on the priorities
Together, we decide what needs immediate attention. You receive a clear scope before any cleanup work begins.
Step 04
Fix and hand back
We repair the agreed issues and show your team what changed and what to watch as the product develops. You pay after the agreed work is complete.
Let a senior engineer review what is really happening inside your AI-built codebase.
We will identify the issues most likely to affect security, stability, and growth, then recommend what your team should address first.
RECENT WORK
Leading Company in Agetech built their MVP with AI and shipped it. 8,000 people signed up in the first week.
WHAT HAPPENED
The app worked. That was never the question.
- 01Then the logins started failing.
- 02Sessions that should have expired did not, and sessions that should have held dropped people out mid-use.
- 03The cost of running it climbed past what each user was worth.
- 04Nobody on the team could explain how the thing was put together, because nobody had written it.
WHAT WE DID
We read it.
- 01Rebuilt the auth flow, so tokens expire when they should and sessions hold when they should.
- 02Took the API keys out of the frontend, where any visitor could have copied them, and moved them to the server.
- 03Moved the stack onto real infrastructure with rate limits, so a busy day could not turn into a bill nobody planned for.
- 04Read every layer again before handing it back.
Result.
- 01The product retained all 8,000 users , 8,000 users retained.
- 02The product retained the users acquired during its first week.
- 03Authentication rebuilt.
- 04Access tokens now expire correctly, and sessions hold up.
- 05Exposed keys removed.
- 06API keys were removed from the frontend, and secrets were moved server-side.
- 07Guardrails added.
- 08The product now has rate limits, basic guardrails, and more suitable infrastructure.
AI can build fast, but a working demo can still hide problems that surface with real users.
We inspect the parts that are easy to miss when building fast with AI, then show your team what needs attention now, what can wait, and what is already in good shape.
Frequently Asked Questions
Questions founders ask before sending their repo.