AI Built It in an Afternoon. We Make It Safe to Launch.
Lovable, Bolt, Replit, Cursor, ChatGPT — the app works, the demo went well, and now real customers and real data are about to touch it. This is the review that happens before that, not after.
AI coding tools are genuinely good, and this page is not an argument against them. The problem is narrower and more specific: they build what you asked for, and they don't build what you didn't know to ask for. Nobody prompts "and make sure a logged-in customer can't read another customer's records by changing the number in the URL." So nobody does.
That gap is where nearly every AI-built application fails, and it fails quietly — usually months later, in front of someone else's data.
Industry security reviews consistently find that a large share of AI-generated code ships with known vulnerability patterns. We wrote about why in AI built your app in 10 minutes — here's what it didn't tell you.
What we find, almost every time
- Authorisation checked in the browser only. The interface hides the admin button; the API behind it happily answers anyone who asks.
- Database rules left open. Row-level security never enabled, so any authenticated user can read the whole table.
- Secrets in the front end. API keys and service credentials shipped in code the browser downloads.
- No rate limiting. A login form or a paid AI endpoint that anyone can hammer, at your expense.
- Inputs trusted. Data written straight to the database or into a query without validation.
- No visibility. No logging, no error tracking, no backups — so when something breaks in production, the first you hear is a customer email.
- Nothing to deploy to. It runs in the builder's preview and there is no real environment, no version control and no way back to yesterday's working version.
How the rescue works
- Audit — fixed price, written report We go through the application properly: authentication, authorisation, data access, secrets, dependencies, error handling and deployment. You get a plain-English report ranked by severity, with the specific file and line for each finding.
- You decide what happens next The report is yours. Fix it yourself, hand it to another developer, or have us do it. There's no obligation and no upsell built into the audit.
- Remediation We fix what needs fixing, in priority order, with each change explained. Critical security issues first, then reliability, then the code quality that decides whether this thing is maintainable in a year.
- Production readiness Version control, a real deployment pipeline, environment separation, automated backups, monitoring and error alerting — the infrastructure the builder never mentioned.
- Handover Documentation of what was wrong, what changed and how to run it. You keep working in your AI tool if you want to; you now just know where the edges are.
Who this is for
About to go live
The app is built and customers are days away. One review before real data arrives is dramatically cheaper than a breach notification afterwards.
Something's wrong
Intermittent failures, data that doesn't add up, or performance that collapsed as soon as more than five people used it.
Investors are asking
Technical due diligence is coming and you'd rather find the problems yourself first. An independent audit is a much better look than being told.
The AI can't fix it any more
Past a certain size, each fix breaks something else and the loop never closes. That's a structural problem, and it needs a person.
What it costs
- $1,500 – $3,500 — fixed-price audit with a written, prioritised report. Most applications land here.
- $3,000 – $12,000 — remediation of critical and high findings, quoted once we know what's actually there.
- $5,000 – $20,000 — full production readiness: fixes plus deployment, monitoring, backups and documentation.
The audit is deliberately standalone. Plenty of people take the report and fix it themselves, and that's a fine outcome.
Common questions
What's actually wrong with AI-generated code?
Usually not the logic — it's the things the AI was never asked about. Authentication checked in the front end but not the back, database rules that let any logged-in user read every record, secrets committed into the code, no rate limiting, and no way to tell when something has gone wrong in production.
Can my app be saved, or do I start again?
Usually saved. The structure AI produces is often reasonable and the gaps are in security, error handling and data integrity — all fixable. We'll tell you honestly if a rebuild is genuinely cheaper, and sometimes it is.
Do I have to stop using AI tools?
No, and we wouldn't suggest it. Keep building with them. The point is to have someone review what they produce before it meets real customers — the same as any other code.
Will you tell me my app is terrible?
We'll tell you what's true, ranked by how much it matters. Most AI-built apps have three or four things that genuinely need fixing and a long tail that doesn't. Knowing the difference is most of the value.
Get it checked before your customers do
Send us the repo or the builder link. We'll tell you what a full audit would involve and what it would cost — and if we spot something critical while scoping, we'll tell you immediately, free.
Request an auditCall 0452 273 155