AI-native apps: the product, not the feature.
An AI-native application is a product that stops making sense when the model is removed: the intelligence sits in the flow of the task, not behind a chat button. We build web, mobile, platform and SaaS products this way.
Web applications
Full products for the browser, built to hold real data, real permissions, and real load.
Mobile applications
Native-feeling apps where the model runs in the flow of the task, not behind a chat button.
Platforms
Multi-tenant systems with the operational tooling required to run them for other companies.
SaaS products
Billing, onboarding, admin, and the AI surface that justifies the subscription.
The product needs the model.
A founder whose product only exists with a model in it
You can describe what the product does for the user, and remove the intelligence and there is nothing left. There is no team on your side to design that product, let alone build it.
A company that bolted AI onto an older interface
The product sells, and the AI sits behind a button nobody presses. The flow was designed before the model existed and now has to be designed around it.
A team with a working demo and no product around it
The model does something impressive in a notebook or a demo account. There is no permissions model, no billing, no admin, and nothing that survives real data or real load. The demo becomes the specification, and the product is built fresh around it.
From product to growth.
- 01
Product
What the product does, and whether it still makes sense with the model removed.
- The product, not the feature
- The AI surface
- 02
Surface
Where the model sits in the task, and which steps the user stops having to take.
- The steps a user drops
- Where the model runs
- 03
Design
Data, permissions, tenancy and evaluation, decided and written before code.
- Documented architecture
- Real permissions model
- 04
Build
The application itself, built to hold real data, real permissions and real load.
- Web, mobile or platform
- Multi-tenant where needed
- 05
Launch
Deployment, monitoring and the first real users, with the operational tooling in place.
- Deployment and monitoring
- Operational tooling
- 06
Growth
Billing, onboarding and admin, then support for six to twelve months.
- Billing, onboarding, admin
- 6 to 12 months of support
Asked before the build.
What is an AI-native application?
An AI-native application is a product that stops making sense when the model is removed: the intelligence sits in the flow of the task, not behind a chat button. Our test is literal: remove the model, and if the product still works, AI was a feature, not the product.
Can you build a SaaS product with AI at its core?
Yes. A SaaS build covers billing, onboarding, admin and the AI surface that justifies the subscription, with the architecture decided and written before code. We run this kind of product ourselves: Annxa, our agentic platform for the aesthetic industry, serves paying customers under their own brands.
Web or mobile first?
Whichever is where the task actually happens. Engagements usually start with one and add the other once the product is proven, and the architecture is written so that is an addition rather than a rebuild.
What happens when the model changes?
The model sits behind a boundary decided in the architecture, so it can be swapped without rewriting the product. Evaluation is in place from the start, so a swap is something you measure rather than guess at.
How do you keep it from being wrong in front of a user?
Guardrails and evaluation are part of the build, not something added after a bad demo. The model works inside your permissions model, and every flow has a defined behaviour for the cases where it has nothing useful to say.
How much does it cost to build an AI app?
There is no list price: an application is priced as one engagement once the product and its model boundary are written down. The figure follows the scope, web, mobile or both, one product or a multi-tenant platform, billing and admin, plus the ownership model and whether deployment is included.
We have a working AI demo. Can you turn it into a product?
Yes, it is one of the cases the service is written for. The demo becomes the specification and the product is built fresh around it, with the permissions model, billing and admin a demo does not have, because we do not build on another developer's code.
Do we own the code?
Yes, if you choose code purchase: you buy the source outright. The default is a use license: we build, own, host and keep evolving the app, and you run it under your brand with full admin access. The model is written into the engagement before work starts.
Bring us the hard part.
The sales conversation is free. Paid consultation is available when the guidance itself is the deliverable.