Our process hasn't changed, but what people bring to the first meeting has changed completely.
Tell us what you have
In 2019, getting an app built meant starting from a whiteboard: mockups, a quick brand, user flows mapped by hand, a scope, and then development. A mid-size product could easily run $200,000 by the time it launched.
Now people come to us with a designed front end, a finished brand, and much of the product already built with AI. Sometimes the whole thing is built and they just don't trust it yet.
We run discovery, build an interactive prototype you can click through and show people, define the first version, and quote the build.
You've designed the product and built the screens with AI tools, so we build the backend underneath it. That means the database, logins and permissions, integrations, and hosting.
AI got you most of the way, so we start by auditing the code. We fix what's broken, rebuild the architecture where it needs it, and get the product ready for real users.
We recently quoted an audit and backend rebuild for a large platform the client had built themselves with AI. It came in at roughly half the cost of building the same platform from scratch, and that kind of project didn't exist a few years ago.
Tell us what you've built
We still follow the same process: discovery, a clear definition of what we're building, then development. What AI changes is how quickly we move through each of those steps.
We use AI design tools to build prototypes that look and feel like your app, so you can click through it before development starts.
Our developers use AI to write and check code faster, and they review and test everything themselves before it ships.
We build AI into client software: document processing, natural-language search, and assistants that work against your own data.
AI is good at producing code that works in a demo. It's less reliable on security, data handling, and architecture that holds up as you grow, so those are the parts we don't hand off to it.
Yes. We use it across our work, from prototypes to code, and we build AI features into the software we deliver.
In discovery, to build interactive prototypes quickly. In development, to write and check code faster. And inside client products, for things like document processing, natural-language search, and assistants that work against your own data.
It is when experienced developers check the work. AI can write code that runs but has security holes or won't hold up as you grow. We review, test, and fix that before anything goes live.
Kind of. You can get a working front end and a lot of the product built. Most people get stuck on the backend, security, and getting it ready for real users. That's usually when they call us.
Because the last part is the hard part. AI does a lot of the heavy lifting, but someone still has to make sure the product is secure, built correctly, and keeps working as it grows.
An idea, a prototype, or a product that's mostly built. We'll get back to you within one business day.