Your AI-generated app is built, but it is not stable enough to trust? If you used Lovable, Bolt, or Replit to create a product and now the app is failing, I can help you turn it into a production-ready system without reconstructing everything from scratch.
These AI builders are great for generating an MVP quickly. The problem is that many generated projects stop there. They often miss critical parts like data integrity, auth logic, deployment setup, API reliability, and security hardening. The result is an app that looks polished but breaks under real conditions.
AI-generated apps from Lovable, Bolt, and Replit often face issues around routing, database behavior, auth flow, broken API requests, and inconsistent state management. The code may be usable in a demo, but it can fall apart when user actions become more complex or when the app reaches a production environment.
Instead of guessing, I investigate the app structure, identify the root cause, and fix the real failure points. That way, your project keeps its original vision while becoming more stable and maintainable.
If your Lovable, Bolt, or Replit project is close but not launch-ready, I can help you fix it. Share the issue and I will review what needs to be repaired before it becomes more expensive to fix later.
You do not need to rebuild the entire product from zero. Often, the right solution is targeted repair, cleanup, and production hardening. That is what I do.
Here is how I approach AI-generated and unstable build projects: I inspect the code, isolate the root cause, and convert the app into a stable, launch-ready system with real-world resilience.
I work across modern and traditional stacks so a project can be repaired without forcing a rewrite when the original idea is still solid.
Backend logic, server routes, request handling, and production security fixes.
Database repair, query troubleshooting, relational data integrity, and table optimization.
Frontend behavior fixes, broken UI logic, async flows, and runtime debugging.
Safer app logic and refactoring for AI-generated frontends that have drifted from working behavior.
Automation scripts, API repair, data processing, and backend debugging support.
Game and app logic repair for scripts, UI flows, gameplay state, and controller bugs.
Refactoring scattered AI output into a cleaner, maintainable codebase that can survive real use.
Version cleanup, safe changes, deployment troubleshooting, and environment alignment.
Each project has its own issues, stack, and constraints, so I begin by understanding what is already working, what is broken, and what must be repaired for launch-day confidence.
Feedback from previous work highlights the value of clear communication, reliable technical delivery, and careful engineering under pressure.
Inbox me now — it’s free to talk. I can review what is broken, explain the likely cause, and tell you the fastest safe path to production readiness.
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