AI prototype to production

Turn an AI-built prototype into a production product.

A prototype can prove that the workflow is possible. Production has a different job. It has to protect user data, survive real traffic, support releases, handle errors, and keep changing without collapsing under early shortcuts.

Expected outcomes

  • A production readiness map for the existing prototype.
  • Clear recommendations on keep, refactor, replace, or rebuild.
  • Launch sequencing for auth, data, payments, integrations, monitoring, and support.
  • A delivery path with the same engineers available after launch.
Who this is for

Best fit

Founders with a working demo

You have something clickable, maybe even impressive, but you do not yet know whether the architecture, data model, and deployment path are ready for customers.

Teams using AI app builders

You used Lovable, Bolt, Replit, v0, Cursor, Bubble, or a similar workflow to move fast and now need a real product engineering review.

Operators preparing for launch

Payments, onboarding, support, permissions, analytics, and release management now matter as much as the screens themselves.

Risks

What usually breaks

The happy path is overbuilt and the edge cases are missing

AI tools are good at producing visible functionality. They are less reliable at finding the awkward states users hit in production.

Data and permissions are too loose

Early prototypes often blur user boundaries, admin access, private records, API keys, and integration credentials.

The launch path is improvised

Hosting, environments, monitoring, backups, migrations, and rollback paths need decisions before real users depend on the system.

LOJI process

How LOJI helps

1

Audit the prototype

We review the user flow, codebase, data model, integrations, deployment setup, security exposure, and support risks.

2

Separate rebuild from hardening

Not every prototype needs to be thrown away. We identify what can stay, what needs refactoring, and what should be rebuilt before launch.

3

Ship the production path

LOJI can handle the hardening work, build missing product surfaces, prepare deployment, and stay attached after launch.

Questions

Common questions before the first call.

Can LOJI work with a prototype built in an AI app builder?

Yes. LOJI can review prototypes from AI app builders and help determine whether the right next step is hardening, migration, rebuild, or a narrower product release.

Do I have to rebuild from scratch?

Not automatically. The first job is to separate what is good enough from what will become a launch risk.

Can LOJI help after the app launches?

Yes. LOJI's delivery model includes post-launch support and hardening so the product does not get handed off to a new team after release.

AI App Launch Readiness Audit

Find out what your prototype needs before launch.

Send the prototype, repo or export, stack notes, and launch goal. LOJI will help identify what needs to be hardened before users rely on it.