Built something real with Bolt.new, Cursor, Lovable, v0 or Replit and hit the wall at production? We audit what you have, keep what is good, rebuild the spine, and take it live, with the code in your name.
AI builders are genuinely impressive. They get you a working demo in an afternoon. Then you put it in front of real users and it falls over, and you are left wondering what you did wrong. You did not do anything wrong. You hit the production gap, and it catches almost everyone.
When we open these projects the pattern is familiar: demo data seeded on the front end, one monolithic blob with no real backend, keys exposed in the browser, routing that breaks off the happy path, and no auth, validation, tests or deployment worth the name. The tool wrote the visible 80%, but that visible code is often only 40% of the work to a real product. We build the rest.
A fast, honest review of what exists: what is salvageable, what must be rebuilt, and where the security holes are.
We usually keep your approved front end (a real saving) and rebuild the architecture, backend, auth and data layer properly.
A production database with a proper schema, real authentication and authorization, replacing demo data and fake logins.
Keys off the client, authorization checks, rate limiting and validated input, before anyone real logs in.
Payments, email and third-party services wired with real keys and error handling, then tested end to end with mock transactions.
The pipeline, tests and monitoring that make shipping updates routine instead of risky.
Lovable gave you a good-looking app fast. We make it safe and real: database rules.
Bolt.new got you a working prototype in the browser. We give it a real server.
You built it in Cursor and it works on your machine. We review the whole codebase.
v0 gave you an interface that looks finished. We keep it.
Replit let you build and host in one place. We make what you built safe for real users.
We review the code, data model and dependencies and tell you honestly what to keep and what to rebuild.
Real auth, a production database, validation and error handling, the foundation the demo never had.
Security pass, real integrations tested with mock transactions, and compliance for your market.
Tests, monitoring and a deploy pipeline, launched under your accounts, with the code yours.
The mistakes we have seen cost founders the most, so you can avoid them.
The demo running is the starting line dressed up as the finish line. The most expensive version ships with demo auth still in place, so any account can read every other account's data.
AI writes code but tells you nothing about which features matter or how users behave. Code does not make a business succeed; strategy, launch and operations do.
Some prototypes are quicker to rebuild cleanly than to untangle. A short audit tells you which situation you are in before you spend.
If the total budget is a thousand or two, productionising an AI prototype will not work out. We say so honestly rather than take it on and disappoint you.
Yes, this is core to what we do. These tools produce real, standard code, so an experienced team can pick it up, audit it, keep what is good (often the UI) and build the real backend, security and data layer, then ship it, with the code in your name.
Because it was generated to pass a demo, not to survive load, bad input and concurrent users. The happy path works; auth, validation, real data, permissions and error handling, the production gap, were never the tool's job. That gap is normal and fixable.
It depends on how it was structured. Clean output is often worth finishing; a tangled prototype with no data model can cost more to untangle than to rebuild the core cleanly. A short audit answers this before you commit budget, and we tell you honestly.
We usually keep the client-approved front-end design and styling, which saves real time and money, and rebuild the spine: architecture, backend, auth and the data layer. We are explicit about what stays and what goes before we start.
Usually not by default. Common gaps are exposed keys, missing authorization checks, no rate limiting and unvalidated input. Any AI-built app needs a security pass before real users or real data, and that is one of the first things we do.
For a clean prototype, hardening and shipping a solid MVP is often a few weeks. A tangled one can take longer to untangle than to rebuild. The audit tells you which case you are in and gives you a timeline before work starts.
Yes, and we will be honest about it. If the total budget is only a thousand or two, productionising an AI prototype into something real will not work out, and we would rather tell you that than take the project and let you down.
Completely. Source code, repositories, hosting, app store and analytics accounts are in your name. Finishing your AI-built app makes it more yours, not less.