Mobile app development company for iOS, Android, and on-device AI

Mobile app cost depends on a handful of drivers: whether you need iOS, Android, or both; cross-platform or native code; how much backend work sits behind the app; offline sync; payments or in-app subscriptions; device features such as the camera or Bluetooth; AI features; and the admin tools your staff need. One cross-platform codebase usually costs less than two native apps because most of the code is shared. We scope a first release that proves the app's value and give you a fixed price for it after discovery.

A typical first release takes 4–6 months: 2–3 weeks of discovery, 3–4 weeks of design and prototyping, 10–14 weeks of building and testing, and 1–3 weeks for store submission and launch. Leave room for store review, because Apple and Google can reject a build over policy details. Google also requires new personal developer accounts to run a closed test with at least 12 testers for 14 days before launch, one more reason we publish under an organization account in your company's name.

Choose cross-platform unless you have a specific reason not to. React Native and Flutter both produce fast, native-feeling apps from one codebase, which means one team, one feature set, and features that reach iOS and Android together. React Native suits teams already using TypeScript and React on the web, and Flutter shines with highly custom, animated interfaces. Go native with Swift or Kotlin for heavy AR or 3D, advanced camera or audio processing, deep hardware integration, or an app that only needs one platform.

You do. We set up your Apple Developer Program and Google Play Console accounts as organization accounts in your company's name, which requires a D-U-N-S number (a free business ID from Dun & Bradstreet), and add our team as members. The code lives in your repository, signing keys sit in your accounts, and the backend runs in your cloud. If you change developers, you keep the app, its reviews, and its users. Apps published under an agency's account are a common trap that makes switching painful.

Use on-device AI when privacy, offline use, or per-request cost matter most, and cloud AI when you need the most capable models. On-device options such as Apple's Foundation Models framework, Core ML, and Google's ML Kit keep data on the phone and cost nothing per request, but the models are smaller and some features need newer phones. Cloud models from OpenAI, Anthropic, or Google are more capable but add latency and usage fees. Cloud calls always go through your backend, so API keys never ship inside the app, and every user gets rate limits and a fallback.

Plan for ongoing maintenance, because an app nobody updates eventually breaks or gets blocked from publishing updates. Apple and Google ship major OS releases every year, Apple periodically requires builds made with a recent SDK, and Google Play requires apps to target a recent Android API level. Libraries, payment SDKs, and store policies change too. A maintenance retainer covers OS and SDK updates, dependency upgrades, crash monitoring, store policy changes, and small improvements, with larger features scoped separately.

We build to the OWASP Mobile Application Security Verification Standard (MASVS): no secrets in the app, tokens kept in the phone's secure storage (the iOS Keychain or Android Keystore), encrypted traffic, and server-side checks for anything that matters, because a phone is a device you don't control. AI coding assistants speed up routine work such as tests and boilerplate, but every change gets human code review, automated tests, and dependency scanning before it merges, and we use business-tier tools that don't train on your code.