Launchr

Your AI-built app almost works.
We do the last stretch.

Lovable, Bolt, Cursor, Replit, v0, ChatGPT — these tools are genuinely good at getting you 80% of the way. The last 20% — auth that holds, a backend that’s really wired up, security, a deploy that sticks — is real engineering. That’s our whole job: a US$29 scan that names every problem in plain English, then fixed-price repairs, re-checked and receipted.

Get the US$29 scan →

Rob’s the front door: press straight through, or tell him what’s wrong first. You sign in by email before the scan starts. Talking is free — the US$29 is refunded after any Fix is accepted. Not sure yet? Run the free one-minute site check first.

Where each AI builder gets stuck

These tools are good. The wall is the same every time — not because you did it wrong, but because the last stretch is real engineering. Here is what we actually find, by tool.

Lovable

Describe your idea and it scaffolds a real React + Supabase app in minutes. For getting from zero to something you can actually see, it is one of the best tools there is.

  • Supabase wiring — the tables exist, but rules, policies and relationships were never finished, so data saves for you and vanishes for everyone else
  • Auth that demos fine but breaks under real users — password resets, sessions, role rules
  • Edge functions and integrations stubbed in but never completed
  • The last mile: custom domain, environment secrets, and a production deploy that sticks
Bolt

Brilliant for speed — a full-stack app running in your browser before your coffee goes cold. As a way to get a working start, it is hard to beat.

  • Moving off the sandbox — what runs inside Bolt’s environment often breaks on a real host
  • Environment variables and API keys hard-coded just to make the demo work
  • Dependency drift — one regenerate and previously working parts quietly break
  • A database that never got past sample data
Replit

Code, database and hosting in one place, and real apps genuinely ship from it.

  • Costs and limits that bite once real users arrive
  • Background jobs and scheduled tasks that stop when the tab does
  • Data living in Replit’s database with no migration path out
  • Secrets and auth configured for development, not production
v0

Generates genuinely beautiful React interfaces — the front of your app can look world-class in an afternoon.

  • It is front-end first: the screens exist, the backend often does not
  • Buttons and forms wired to placeholder handlers that go nowhere
  • No auth, no database, no payments — the hard 60% is still to build
  • Assembling the generated pieces into one coherent, deployable app
ChatGPT and Claude

Plenty of people build their first app by asking a chat assistant to write the code — and honestly, it writes decent code.

  • The code lives in a chat thread — no repo, no versions, files pasted into folders by hand
  • Each new answer subtly disagrees with the last, so the pieces do not quite fit
  • It runs on your machine but was never deployed anywhere
  • No security pass — secrets sitting in the code, inputs unvalidated
Cursor

A serious tool — a real editor with AI beside you, and plenty of working software gets built in it.

  • The context wall: once the project grows, each AI edit fixes one thing and silently breaks another
  • No tests — so regressions ship invisibly
  • Half-finished refactors layered over each other until nobody knows what is live
  • It runs on your machine — and was never deployed anywhere else

Built it somewhere else? The scan does not care what wrote the code — it reads what is there.

The pattern — measured, not guessed

We run an AI build factory ourselves and publish our numbers. Across our last 403 builds (17 Jun – 22 Aug 2026), 27.5% could not reach a working, shipped state without a human stepping in — 37.8% for apps with real backends. And the most common root cause, by a mile, is a front end that looks finished but never properly talks to its backend. Industry-wide it’s no better: one scan of 5,600 live AI-built apps found 2,038 critical vulnerabilities. None of this means the tools are bad. It means the last stretch is real engineering.

How the fix works

1. The US$29 scan

We read your app end to end and name every defect in plain English — security, wiring, broken flows. The US$29 is refunded after any Fix is accepted.

2. You approve the scope

You see the verdict, the exact findings and the fixed price before you commit — Quick Fix US$149, Rescue US$299, Launch Ready US$599.

3. Fixed, re-checked, receipted

Every approved finding is closed, verified end to end, and receipted — then it’s handed back running. Yours: code, accounts, everything.

✓Our guarantee: the scan names every problem it finds — and every finding in your accepted fix scope is closed, re-checked and receipted, or you don’t pay for that fix. No moving goalposts: the findings you approve are the job.

Half-built rather than broken?

If your app is stuck at “80% done, forever” rather than broken, start at finish my app — same scan, same honesty, pointed at completion instead of repair. Or see the full Launchr Fix service.

Straight answers

Which tools do you fix apps from?

Any of them. The pages here cover Lovable, Bolt, Cursor, Replit, v0 and ChatGPT because that’s where most stuck apps come from — but the scan reads code, not logos. If an AI wrote it, we can scan it.

What does the scan actually give me?

A named-defects report in plain English: every problem found, what it means, and what it takes to fix — with a fixed price. US$29, refunded after any Fix is accepted. You’ll know exactly what’s wrong before you spend another dollar.

How much do fixes cost?

Fixed prices, agreed before work starts: Quick Fix US$149, Rescue US$299, Launch Ready US$599. Bigger jobs are quoted separately and honestly — no hourly meter.

What if it can’t be fixed?

Every finding in your accepted scope is closed, re-checked and receipted, or you don’t pay for that fix. And if a rebuild would genuinely be cheaper than a repair, the report says so plainly.

Proof, not promises

A rescue, receipt and all.

Worked examples, not clients — real apps we built, let break the way real apps break, then rescued. Every credential in them was deliberately seeded and isolated for the exercise: no customer, no production account and no real data was ever exposed. No borrowed logos, no mystery scores: here's what the scan found, and proof every defect is closed.

Plantyplant-watering app · 7 files
Before · D

Looked finished. Wasn't. The scan named 7 problems in plain English:

  • A hardcoded GitHub token sitting in the code — caught three independent ways. A password anyone could read.
  • Cross-site scripting — a booby-trapped link could run code in a visitor's browser.
  • The plant name saved & shown without cleaning — the same door, a second way in.
  • That hole also broke the greeting on normal use — dangerous and broken.
7 named · 7 closed · 0 still there

Every defect re-checked one at a time — by the same tool that found it. Not a new score. A receipt.

BookWellappointment booking admin · Node/Express/SQLite
Before · F

Ran fine. Was a security disaster. The scan named 44 problems — the worst of them:

  • A deliberately seeded Stripe-style secret key sitting in the source — alongside the database password and the JWT & SendGrid keys.
  • Three SQL-injection holes — a crafted name could read or wreck the entire bookings table.
  • An admin endpoint with no login — anyone could pull every customer's bookings.
  • Wildcard CORS with credentials, a guessable session token, and two cross-site-scripting holes.
15 critical holes named · 15 closed · 0 still there

Every key, injection and XSS shut — each re-checked by the tool that found it. The honest bit: the wider mess earned a rebuild verdict, so the rest went to a human, not a faked fix.

Cartsyonline store · Node/Express/SQLite
Before · F

A working shopfront — and wide open. The scan named 47 problems; the standouts:

  • A seeded Stripe-style key and an AWS-style access key sitting in the source.
  • Client-controlled pricing — a shopper could pay 1¢ for anything by editing the request.
  • Three SQL-injection holes, plus an order page with no ownership check — read anyone's order.
  • Stored XSS in product reviews, wildcard CORS, a guessable session token.
12 critical holes named · 12 closed · 0 still there

Every leaked key and injection shut — re-checked by the tool that found it. The trickier logic holes (pricing, access checks) earned a rebuild flag and went to a human.

See a full reportthe real thing, start to finish
📄

Curious what the scan actually hands you? Here's a real 44-finding report — the grade, every problem named in plain English, and exactly how to fix each one.

  • Graded, with an honest verdict — worth fixing, or not.
  • Every finding by severity: security, bugs, quality, performance.
  • Leaked secrets auto-redacted — safe to read and share.
  • Print it or save as a PDF in one click.
Open the sample report →

Exactly what a client receives after a scan.