Built with Base44

Your Base44 app has hit its ceiling. Here is what that costs.

Base44 is fast because it decides the data layer for you, and that is the same reason it stops. What comes to us is almost never a crash: it is an app that works and cannot become the next thing you need it to be. The audit's job here is to tell you honestly which.

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What usually breaks in Base44

The data model cannot carry a second kind of user

Everything was built around one sort of account, so records belong to the app rather than to anybody in particular. Adding a client alongside a staff member, or an organisation above both, means a notion of ownership that nothing currently has. Every screen reads from that assumption, which is why this is not a small change.

Roles are an if-statement in the interface

An admin sees more because a condition in the page hides the rest. The underlying reads are identical for everyone, so the data is one request away from any account that thinks to make it. It behaves correctly for honest users, which is not the same as being enforced.

The demo's shortcuts became the schema

Statuses kept as free text, dates as strings, several facts crammed into one field because it was quicker to show that way. Reports and filters are now built on values nobody can constrain, so a typo makes a new category and the totals stop agreeing with each other.

Getting the project out means starting over

The data can be exported; the behaviour cannot, because it lives in the platform rather than in files you hold. Leaving is a rebuild rather than a migration, and the useful thing to know is what that costs today, while the app is small, rather than next year.

Symptoms we see most in Base44 projects

Is there anything you can fix without leaving the platform?

Yes, more than people expect. Ownership can often be introduced on the existing records, and a free-text field can be cleaned up and constrained. We do that work in place and say plainly which of your goals it does and does not reach.

If I do have to move, does anything survive?

Your data does, and so does every decision you have made about how the thing should work, which is most of the value and none of the cost. What gets rebuilt is the screens and the rules. The audit prices that rebuild so the choice is a number rather than a feeling.

How do I know the audit will not recommend a rebuild anyway?

Because it is the answer we like least: it is a bigger job, it takes longer to say yes to, and we would rather sell you the repair. When the platform genuinely cannot express what you need, you get told that with the reason, and you are free to take the findings elsewhere.

How it works

Audit

$199~~$349~~promo

You send a link, a repo, or both. We reproduce the problem, read the code, and record a short walkthrough: what's broken, why it broke, and what it takes to fix. You get written findings and a fixed quote.

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Full Fix

Priced after the audit

Scoped from the audit and agreed before anything starts. We fix the cause rather than the symptom, and hand back something maintainable, with a written note on what changed and why.

Nobody can price this honestly before seeing the code. The audit is what makes a firm number possible.

The audit is a fixed price and you know it before you pay. Everything after it is quoted from what the audit actually found, and you approve the number before any work starts.

Why trust us with it

What we can show you is who does the work, what it costs, and how well we already know the failure you are staring at.

A desk at night, the walkthrough being recorded

A small agency, not a marketplace

This is run by a small web agency. The person who records your audit is the person who does the fix, so you're not being routed to an anonymous bidder.

$199~~$349~~promo

The audit stands on its own

Plenty of people take the findings and do the work themselves, or hand them to their own developer. That is a fine outcome and nothing is bundled to stop it.

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Fixed price, agreed up front

You approve a number before work starts. If the job turns out harder than we estimated, that's ours to absorb, not a change order.

Built with one of these? You're in the right place.

Lovable: Lovable projects usually break at the Supabase edge: environment variables that never reached production, or row-level security left open on a table that holds real customer data.
Bolt: Bolt ships fast and leaves the build config behind. The deploy fails on a missing package, a Node version, or an API key that only ever existed in the preview.
Replit: Replit apps run fine in the workspace and 500 on a real domain: ports, file paths and secrets that were never wired up for the deployed process.
Cursor: Cursor edits confidently across files it has not read. Two features end up disagreeing about the same state, and the bug moves every time you fix it.
v0: v0 gives you the interface, not the wiring. Forms post to nothing, server actions are still stubs, and auth is a component rather than a session.
Windsurf: Windsurf refactors reach further than intended. Imports, types and routes drift apart until the build stops on something unrelated to what you changed.
Base44: Base44 apps hit their ceiling at data and roles: the model that fit the demo cannot carry a second kind of user without redoing what sits underneath it.
Claude Code: Claude Code writes real code, which means real dependencies, migrations and tests. When it breaks, it breaks somewhere prompting cannot reach.

What it usually turns out to be

It works locally, then 500s once deployed: Nearly always an environment variable, a build step or a file path that only exists on your machine. The code is usually fine.
The AI keeps fixing the same bug: Each pass patches the symptom because the cause sits a layer down, in the data model or in how state is shared. Prompting harder does not reach it.
Forms submit but nothing arrives: The browser gets a success back while the server quietly fails. Without error handling and logs nobody finds out until a customer complains.
Logins drop or leak between users: Session and auth code copied from an example built for a different rendering model. It looks right in testing and breaks under real traffic.

And what nobody notices until later

Security is the part an AI builder is quietest about. None of these stop the app working, which is exactly why they ship.

The database is open to anyone with the URL: Supabase and Firebase hand the browser a key on purpose — the row policies are what actually guard the data. Generated projects routinely ship with those policies off, which turns a public key into a key to everything.
Secrets that shipped to the browser: A service key pasted into a component, or one prefixed NEXT_PUBLIC_ so the build would stop complaining. It is in the page source, readable in devtools, and the bill for it is yours.
Any logged-in user can read every other user's data: The endpoint takes an id and returns that record without ever asking whose it is. Nothing looks wrong while you are the only account; change the number in the URL and you are in someone else's.
Nothing stops the same request a thousand times over: No rate limit and no real validation on the public routes, so login, password reset and checkout can each be hammered until something gives. Generated code almost never adds this on its own.

If you recognised your own problem somewhere above, that is the point. The audit is where you find out which one it actually is.

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$199~~$349~~promo

Send it over. We'll tell you what's wrong.

One fixed-price audit at $199 instead of $349. A video walkthrough, written findings and a firm quote on what it takes to fix.

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