
United States
Your prototype works. It also has hardcoded secrets, unprotected API routes and no tests, and you probably found that out the hard way. We audit AI-generated codebases, fix what is actually dangerous, and hand you back a product you can put in front of real users.

Vibe coding, meaning you describe what you want to an AI tool and ship what it returns, genuinely works for the first version. You got a working product in a weekend that would have taken a contractor two months. That leverage is real, and we are not here to tell you it was a mistake.
The problem is that AI coding tools optimise for code that runs, not code that survives. Veracode's 2025 GenAI Code Security Report tested more than 100 models across 80 coding tasks and found roughly 45% of AI-generated code introduced an OWASP Top-10 vulnerability. The failures cluster in exactly the places a demo never exercises: authorization, secrets handling, payment flows, and error paths.
A vibe code rescue is the structured process of finding those failures before your users do, then fixing the ones that actually matter, in priority order, without throwing away the product you already have. Most of the apps we see do not need a rebuild. They need about two weeks of senior engineering attention on the parts nobody prompted for.
Exposed Secrets
API keys, database URLs and service tokens committed to the repo or shipped to the browser bundle. We find them, rotate them, and scrub the git history so an old commit can't leak them later.
Unprotected API Routes
The most common failure we find. Authorization gets checked in the UI but never on the server, so any logged-in user can read any other user's data by changing an ID in the URL.
Silent Error Paths
AI-generated code wraps external calls in empty catch blocks. Payments fail quietly, emails never send, and nothing shows up in a log. We add structured handling and real error tracking.
No Safety Net
No CI, no tests, no staging. Every deploy is a live experiment. We add a pipeline that runs on every push and end-to-end tests on your three to five money paths.
Data Model Drift
Schemas grown one prompt at a time: duplicated tables, missing indexes, no foreign keys. This is the one that gets expensive later, so we assess it first and tell you honestly if it needs restructuring.
Runaway Cost & Latency
Unbounded LLM calls, no caching, no rate limits, N+1 queries on every page load. Fine at ten users. A five-figure bill at ten thousand.
WHAT IT COSTS
Every competing rescue page says "contact us for pricing". Here are our actual numbers. The audit fee is credited in full against a rescue if you go ahead.
$1,500
3 business days · fixed price
A senior engineer reads your codebase and gives you a written report: every security and stability risk found, ranked by severity, with the effort to fix each one. You get the report whether or not you hire us for the fix.
from $6,000
2 weeks · fixed scope
The fix itself. We work through the audit findings in severity order and hand back an app that is safe to put in front of paying users. Same product, same features, without the landmines.
from $18,000
4 to 8 weeks · milestone-based
For the cases where the foundation genuinely cannot hold. We keep your product and your data, and rebuild the layers underneath on an architecture that supports the next two years instead of the next two months.
HOW IT RUNS
You show us the app and tell us what broke. We tell you straight away whether this is a two-week fix or a rebuild, and roughly what it costs. No deck, no discovery invoice.
Read-only access to the repo. A senior engineer runs the full diagnostic and writes up every risk with a severity rating and a fix estimate. You own the report.
We start with anything that leaks data or loses money, then stability, then structure. You see a working build at the end of every week, not at the end of the project.
Your repo, your cloud accounts, your data, throughout. You get a written handover covering what changed and what to watch, so your next developer isn't starting blind.
The full diagnostic, free. Six checks you can run on your own codebase in about 30 minutes, and how to read the results.
If you haven't built it yet: a fixed-scope sprint that gets you a production-ready MVP without the cleanup bill afterwards.
Longer-term product engineering once the rescue is done and you're ready to build on a foundation that holds.
Let's discuss how we can create a custom GPT-powered solution tailored to your specific needs and industry challenges.
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