AI mobile apps

Mobile apps where AI features feel native: quick, considerate of privacy, and still useful when the connection drops. Built for iOS and Android from one codebase where that makes sense.

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The problem

On a phone, AI features have extra constraints. Slow responses feel broken, sending everything to a server may not be acceptable, and people use apps on trains and in basements.

We design AI features around those limits: what runs on the device, what runs on a server, and what the app does when neither is available.

What you get

  1. A cross-platform app

    One codebase for iOS and Android where it fits, native where it matters.

  2. AI features designed for mobile

    Camera and document scanning, voice input, assistants and search, with clear loading and offline states.

  3. A backend you control

    APIs, data and AI calls on infrastructure in your account.

  4. Store submission support

    Builds, store listings and privacy disclosures prepared with you.

Example scenarios

Illustrations of the kind of work involved, not client case studies.

Field technicians

Today
Technicians call the office to look up manuals and past repairs.
With AI
They photograph the equipment label and ask the app, which answers from the company’s manuals and repair history.

A retail brand

Today
Customers scroll a large catalogue to find the right item.
With AI
They describe what they need, and the app suggests products that are actually in stock nearby.

Questions

Can AI features run offline?

Some can, using on-device models. We decide feature by feature, based on what the device can handle and how sensitive the data is.

Do you publish to the App Store and Google Play?

Yes, under your developer accounts, so the apps stay yours.

Tell us what you are trying to do.

A few sentences are enough. We will reply by email with questions or a suggested next step.

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Other services

  1. AI-powered websites

    A fast business website with an assistant that answers, qualifies and books.

  2. AI web apps

    Internal tools and customer products where AI handles a real part of the work.

  3. AI integration for businesses

    Assistants, knowledge bases and automations connected to the tools you already use.

  4. AI strategy and prototyping

    Find out what is realistic, and test it on your own data before committing to a build.