iOS and Android apps built by people who have shipped them through review before, including the parts that catch teams out: signing, staged rollout, privacy declarations and the first submission. Native or cross-platform is a trade-off we make per project and explain, not a preference we bring with us. Offline behaviour is designed rather than discovered, because a phone loses signal and what happens next is a product decision. On-device AI goes in where latency, cost or privacy genuinely justify it, and stays out where it does not.
The same four moves on every engagement of this kind. No discovery phase that bills for months before anything runs.
We agree the platforms, the offline behaviour and the store constraints up front. These decide the architecture, and changing them later is expensive.
Native or cross-platform depending on what the app actually needs, working in your repo, with releases going out on the same fortnightly cycle.
Automated suites plus real hardware, because emulators do not reproduce the battery, network and permission behaviour that gets apps rejected.
We handle submission, signing and staged rollout, then keep shipping. You own the developer accounts and the certificates throughout.
The choice between native and cross-platform is a trade-off, not an ideology. We make it per project, based on what the app actually does, and we tell you what you give up either way.
Phones lose signal. What the app does when that happens is a product question, decided up front, rather than a bug report that arrives after launch from your most frustrated users.
Some inference belongs on the phone for latency, cost or privacy; plenty does not. We measure rather than assume, because on-device is a real constraint on model size and battery.
Signing, build numbers, staged rollout, crash reporting and the review process, automated and documented. The first submission is where unprepared teams lose two weeks.
Have an app that needs to be built properly?
Scope this with usOn a phone the AI question is mostly a constraints question. Battery, model size, network and privacy all pull in one direction, and product expectations pull in the other. Deciding what runs where is the design work.
Latency, offline use and privacy can justify local inference. Model size and battery are the price. We measure both against a server-side baseline instead of assuming.
A defined experience when the network is gone or the provider is slow, because an app that hangs on a spinner reads as broken rather than as busy.
Hands-free capture and on-device transcription are genuinely better on a phone than on a desktop. Most other AI features are not, and we will say so.
Store requirements, privacy declarations and permissions are handled as part of the build rather than discovered at submission.
Dynamic type, contrast and screen reader support are part of how the interface is built. Adding them afterwards means rebuilding the screens.
The API and the app are built by the same people, so the two agree and nobody is blocked waiting on a contract that was never written down.
On your device, through TestFlight or Play internal testing, from the first fortnight. You use it rather than read about it.
The questions that come up most on a first call about this practice, answered the way we would answer them on the phone.
It depends on what the app does. Heavy device integration, sustained performance or platform-specific interaction points to native; most content and workflow apps do not. We recommend per project and show the reasoning.