Built Something With AI
You built something with AI. Now let's make it real.
AI tools can get you a working prototype in a weekend. Turning that prototype into something you can safely put in front of real customers is a different job — and it's the one we love.
It's a genuinely new kind of moment: a founder with no engineering background describes an idea to Claude, ChatGPT, Cursor, Replit, Lovable, Bolt, or FlutterFlow, and a few hours later there's a working app on the screen. That's not a toy — it's a real head start. But there's a gap between "it works on my machine" and "it's live, secure, and taking payments," and that gap is where most AI-built projects stall.
We specialize in taking AI-generated prototypes across that finish line. You keep the vision and the momentum; we add the production engineering — hosting, databases, security, deployment, and the boring-but-essential pieces that make software trustworthy.
Does this sound familiar?
- Your app runs locally but you can't get it reliably online
- There's no real database — data lives in memory or a spreadsheet
- You're not sure it's secure enough to handle real users
- You need to take payments but haven't integrated them safely
- It needs to go into the App Store or Google Play
- Every change you ask the AI for seems to break something else
What the AI got right — and what it left out
AI coding tools are excellent at generating features and interfaces. They're much weaker at the things that don't show up in a demo: secure authentication, a proper database, error handling, backups, deployment pipelines, rate limiting, and the dozens of edge cases real users create. None of that is visible when you're clicking through a prototype, which is exactly why it gets skipped.
The result is a common pattern — a beautiful prototype that can't safely go live. The fix isn't to throw the work away; it's to keep what the AI built and add the production layer underneath it. That's faster and cheaper than most people expect, because the hard creative work of shaping the product is already done.
How we take it to production
Foundation
- Reliable hosting and deployment
- A real, backed-up database
- Secure user accounts and authentication
- Environment and secrets management
Trust & safety
- A security review before you launch
- Input validation and abuse protection
- Privacy and data-handling done properly
- Monitoring so you know when something breaks
Going to market
- Payments and subscriptions via a proper payment integration
- App Store and Google Play publishing
- Scaling so it holds up as users arrive
- A sane process for shipping future changes
Ongoing
- Maintenance and updates as platforms change
- A partner to call instead of fighting the AI
- Clear documentation of how it all works
- Room to grow features without breaking things
Who we help with this
- Non-technical founders who prototyped with AI
- Solo builders who got 80% there and stalled
- Small teams shipping an AI-assisted MVP
- Consultants productizing a tool they built for themselves
- Anyone told "it's basically done" who suspects it isn't
Questions we hear a lot
Got a prototype that's almost there?
Show us what the AI built. We'll tell you honestly what it takes to launch it for real.