It depends on the size of the app and what the audit finds, but it's often far less than building from scratch. On a recent large platform a client built with AI, our audit and backend rebuild came in at roughly half the cost of building it from scratch.
Fixing an app you built with AI is usually far cheaper than building the same thing from scratch. What it costs depends on the size of the app and what our audit finds.
A few years ago almost nobody came to us with a nearly finished product they had built themselves. Now it happens regularly. AI tools do a lot of the heavy lifting, and people get most of the way there on their own, often with a designed front end, a working prototype and sometimes a backend that seems to run fine.
What they need from us is different. They do not need a full build to launch an MVP. They need someone to check the work, fix it and set it up correctly, and they reasonably want to know what that costs before committing.
A recent example
A client built a large platform on their own using AI. They did not trust it enough to launch, so they asked us to audit everything and rebuild the backend architecture properly.
Our quote came in at roughly half of what it would have cost to build the same platform from scratch.
Not every project lands at half. Some apps need light fixes and some need more rebuilt than kept. The audit is how you find out, and more importantly, how you avoid major bugs, errors and critical security gaps down the road.
Why AI-built apps need a second look
AI is very good at producing software that works in a demo. You click through it, the screens load, the data shows up and it feels finished. The problems show up later, when real people use it in ways nobody tested, or when more people arrive than the app was designed to handle.
That is not a knock on AI tools. It is the difference between software that runs and software that is ready for customers, their information and often their money. Closing that gap is mostly about the parts you cannot see from the screen, which is exactly why they are so easy to miss.
What an audit looks at
We review the code, security and architecture, and in practice that comes down to a handful of plain questions.
We ask whether it is secure, meaning who can log in, what each person is allowed to see and change, and whether passwords, keys or customer information are exposed anywhere they should not be. We ask whether the data is handled properly, which covers how the database is structured, whether information is stored in a way that will still make sense as the app grows, and whether there is a plan for backups if something goes wrong.
We ask whether it will hold up, meaning whether the app can handle more people and more data without slowing down or breaking, and whether the hosting is set up for a real launch rather than a test. Then we ask whether it can be maintained, which comes down to whether the code is organized well enough that a developer can fix a bug or add a feature without breaking something unrelated.
What the work covers
The audit comes first, and we review the code, security and architecture. Then you get our findings, which is a plain answer on what is sound, what needs fixing and what should be rebuilt.
Those findings become a Scope of Work with milestones, a timeline and a cost, so you know exactly what you are agreeing to before the fixes begin. The hardening itself is the last part. We fix bugs, close security gaps, rebuild the parts that will not hold up and set it up correctly, and our developers review and test the code before it ships.
What drives the price
Size is the first factor, since more screens, more features and more data always increase complexity and cost. The backend is usually the biggest piece of the work, so if the database, logins and permissions need rebuilding, that is where the hours go.
Security is the third factor, because apps that handle payments or personal information need more review for compliance. How the app was built matters as well. Some AI-built code is close to right, and some has to be replaced before it can be fixed.
Common problems in AI-built apps
Every app is different, and a few issues come up often enough in AI-generated code that they are worth knowing about before an audit starts.
Checks that only happen on the screen are the most common. An app might hide a button from people who should not use it, while the system behind it still lets anyone make that request directly.
Secrets in the wrong place are close behind. Keys and passwords for connected services sometimes end up written into the code itself, where they are far easier to find than they should be.
Then there is the database built for the demo. Tables that work fine with a few test records become slow or tangled once real information starts piling up. The same logic written several times causes similar trouble, because when an AI tool solves the same problem in different places, a change in one spot does not carry over to the others. That is how small fixes turn into new bugs. Missing tests, backups and monitoring are the last pattern we see, and they usually mean problems get discovered by customers first.
None of these mean an app has to be thrown away. They are the kinds of issues an audit is designed to catch while they are still relatively inexpensive to fix.
When rebuilding makes more sense
If the audit shows most of the app needs replacing, we will tell you. Sometimes the fastest path is to keep your designs and product thinking and rebuild the code underneath, and your work still counts, because it becomes the blueprint for the rebuild.
That can still be a good outcome. The hardest part of most software projects is working out exactly what to build, and if you have done that with AI, you have already covered a lot of the ground that usually happens in discovery. For what a build from scratch costs, see how much custom software costs.
What happens after hardening
Once the fixes are done, you have an app you can launch with confidence and keep improving. That usually means moving toward a real release, putting it in front of customers and learning from how they use it.
Software keeps needing attention after launch, because the services and devices it relies on keep changing, and your customers will ask for things you did not plan for. We provide support and maintenance for every project we build, and we talk through that pricing as the work nears completion, so you are not left working out what comes next on your own.
It is also a good moment to decide how you want to keep building. One approach we like is to keep using AI tools to explore early ideas, then have experienced developers review and build the features that actually go into the product.
How to prepare for an audit
A little preparation makes an audit faster and our findings more useful.
Give us access to everything, meaning the code, the hosting account, the database and any connected services like payment or email providers. Send us your notes on what is working and what is not, because even rough notes help, especially about anything that has already given you trouble.
Tell us who the app is for and when you want to launch, since knowing your users and your timeline helps us focus on what matters most for your first release. Tell us what you built it with too, because the AI tools, templates and services you used tell us a lot about where to look first.
Then give us your priorities if the budget is tight. If you cannot fix everything at once, tell us what matters most for launch, whether that is security, a particular feature or getting in front of customers quickly, and we will sort the findings around what you need first.