AI inside your iOS app
AI that feels at home in your iOS app.
We build AI features into iPhone and iPad apps — assistants, summaries, smart search, suggestions — natively in Swift and SwiftUI, running on the device, on your servers, or both.
An example iOS expenses app: the user asks what they spent on client dinners this month. The assistant finds four receipts, notes that two are missing a project code, and offers to add them, which the user taps.
What it is
An AI feature on iOS has to meet the standard of the rest of the platform: fast, private by default, and quiet when it has nothing useful to say. We design it around your app’s patterns, choose what runs on the device and what runs on your servers, and ship it through App Review like any other release.
This page is one part of AI inside your product. The same service covers web and Android apps.
The spec
- What you get
- AI features built natively into your iOS app, in Swift and SwiftUI
- On-device models with Core ML where privacy or speed matter, server models where quality does
- Fallbacks and offline behaviour, so the app still works without the AI
- Monitoring for quality, response time and cost once it is live
- How we measure it
- Task success for real users, response time on the iPhones they actually carry, and cost per active user — tracked in production against the bar we agree first.
- A good first step
- Pick the screen where your users spend the most effort. We prototype the AI feature there and test it on real devices.
What we build with
Our usual iOS stack. We work inside your codebase and conventions.
- Swift
- SwiftUI
- UIKit
- Combine
- Core Data
- Core ML
- Vision
- Natural Language
- CloudKit
- Your backend APIs
Where it fits
Examples of what this work looks like — not client stories.
- Example
Search that understands
Find a note, a payment or a photo by describing it, instead of remembering the exact word.
- Example
Document capture
Scan a receipt or a form and get the fields that matter, checked by the user before anything is saved.
- Example
Private summaries
A short digest of the user’s own activity — spending, workouts, messages — worked out on the device.
- Example
An in-app assistant
Help that knows the user’s account and your product, and hands off to a person when it should.
Common questions
For many tasks, yes, with Core ML and Apple’s on-device frameworks. Larger tasks usually run on your servers. We measure both on your data before deciding.
We follow Apple’s guidelines on AI features, privacy labels and user data from the start, and handle review like any other release. Nobody can promise an outcome, but we design so that there are no surprises.
Yes. We work inside your codebase and release process, and your team reviews and owns everything we ship.
On-device features keep the data on the phone. Server features go through your backend, under the provider terms you choose — including no training on your data.
What should AI do in your iOS app?
Tell us the feature and who uses it. We will come back with how we would build it, where it should run, and how we would measure it.