Apps built with Lovable, Bolt, Replit or Cursor usually work in a demo, then break with real users. These are the problems we keep finding:

API keys sitting in the frontend code

Login checked only in the browser, so anyone can read other users' data

Database rules left open (for example Supabase row-level security switched off)

No rate limits, so one bot can run up your Supabase or OpenAI bill

No backups, no logging and no way to know when something breaks

Payments that can be skipped or faked from the browser

Fine at 50 users, down at 5,000

You don't need to start over. We keep what works and harden what breaks.

Founders who built an app with AI tools and are about to launch or take payments

Products that already have users and are starting to see errors, slowdowns or surprise bills

Teams that want to keep building fast with AI tools, with a safety net underneath

You share the app and the repo. Read access is enough to start.

Audit. We review security, authentication, database rules, payments, performance, hosting and running costs.

Prioritised fix list. Every issue ranked by risk, explained in plain language, with what it costs to fix.

Fix and harden. We fix the critical issues, add backups, monitoring and rate limits, and set up proper deployment.

Hand back, ready for launch. You get the fixed app, a report of what changed, and guardrails so new AI-generated code doesn't reopen the same holes.

Secrets moved to the server, with keys rotated

Server-side authentication and access rules on every request

Rate limits and spending caps on paid APIs

Automated backups and error monitoring

A deployment pipeline with a staging environment

Performance fixes so the app holds up as users grow

We've done this at scale: an EdTech platform we took from 20K to 250K daily users, 10M+ requests a minute, with zero downtime through three migrations. 50+ products shipped, and every fix reviewed by senior engineers.