Mobile app development for iOS and Android

How much does mobile app development cost?

Three things drive the price: the number of screens and flows, the amount of business logic and whether the app needs its own backend. A simple single-platform app with a few screens and data from an existing API starts at €1,500. An iOS and Android app with sign-in, push notifications, offline mode and analytics starts at €3,000, and business apps with a backend, admin panel and integrations at €6,000.

Beyond development, plan for running costs: an Apple developer account is USD 99 per year, a Google Play account USD 25 one-off, and backend hosting depends on your user count. The biggest mistake is budgeting only for version one. Good apps evolve in phases, so we recommend splitting the budget between a first release and a few months of improvements based on real usage.

Price is also shaped by decisions that are easy to overlook: whether the app needs several languages, whether users have different roles and permissions, whether a tablet layout is required and whether data must stay on EU servers. That is why we run a short workshop before quoting and go through these items one by one. You get a specification with a feature list, a per-phase estimate and clear boundaries for version one, so the budget does not shift mid-project.

Native or cross-platform development?

Native apps are written separately for each platform, in Swift for iOS and Kotlin for Android. They offer the best performance and immediate access to new OS features, but mean two codebases, two builds and higher maintenance costs.

Cross-platform frameworks, React Native and Flutter, let most of the code be shared across both platforms. For the vast majority of business apps, such as shops, bookings, field and loyalty apps, the speed difference is invisible to users, while development and maintenance cost far less.

The decision should follow features, not trends. If the app relies heavily on Bluetooth devices, real-time video processing or advanced system widgets, going native saves time later. If the focus is forms, lists, maps, payments and notifications, cross-platform delivers the same quality for less money. It also matters who will maintain the app: one team with one codebase keeps both platforms in step and ships new features to iOS and Android on the same day.

• We choose cross-platform for business apps, e-commerce, bookings and internal tools.
• We choose native for demanding graphics, heavy audio and video processing or deep hardware integration.
• A mix is common: shared code with native modules for camera, Bluetooth or payments.

What goes into a business app

Users only see screens, but there is much more behind them. Most apps need a server that stores data and runs business logic, an admin panel where your team manages content and users, a notification system and connections to existing software, from ERP and CRM to payment and courier services.

That is why we start every project by mapping the whole system, not just designing screens. Everyone knows upfront what gets built, what it costs and who is responsible for what, and you do not have to coordinate three different vendors.

We pay particular attention to security and privacy. Communication between app and server is encrypted, sensitive data on the device lives in the system's protected storage, and access is controlled with roles and short-lived tokens. For businesses that process personal data we align the app with GDPR: we state clearly what data is collected, allow account deletion from inside the app, as both Apple and Google require, and keep access logs.

What publishing on the App Store and Google Play looks like

Every app goes through review before release. Apple checks the app against its guidelines, which usually takes one to a few days, and the most common rejection reasons are an unclear privacy policy, incomplete data collection disclosures and features that cannot be tested without a demo account. Google Play review is usually faster, but new personal developer accounts must run a closed test before public release.

We prepare everything the stores require: a title and description optimised for store search, screenshots, the icon, a privacy policy, data safety declarations and demo accounts for reviewers. The app is published on your developer account, so you own it from day one.

After the first release, new versions move much faster. We use automated builds and staged rollouts to a small share of users first, so any issue is caught before it reaches everyone. For internal apps that should not be public there are private distribution channels, so only your employees receive the app, with no public store page.

Maintenance and updates after launch

A mobile app is not finished on release day. Apple and Google ship new OS versions and change requirements every year, and apps that are not updated eventually stop meeting store rules or start behaving unexpectedly on new devices.

Maintenance covers crash and error monitoring, library and security updates, adapting to new iOS and Android versions and small changes based on user feedback. Analytics shows where users drop off, so we plan the next versions on data rather than assumptions.

We recommend agreeing on maintenance together with development, with a defined response time for critical bugs and a monthly pool of hours for small changes. That way the app never waits months for a fix because no team is on contract. Every few months we also run a short review of what users rely on most, where errors occur and which features are worth adding, so the app keeps serving your business goals.

AI features in a mobile app

AI in an app makes sense when it shortens the user's work: an assistant that answers from your knowledge base, a form filled automatically from a document photo, or computer vision that recognises a product, damage or a licence plate.

For this we use our own fine-tuned models. Smaller models run directly on the phone, so they work offline and send data nowhere, while heavier tasks are processed on your private server. Your users' data stays under your control.

A good AI feature starts with data. We adapt the model on examples from your business, such as your documents, product photos or typical customer questions, and measure accuracy before it goes into the app. When the model is unsure, the app says so clearly and leaves the decision to the user or an operator. That way AI speeds work up instead of creating new mistakes someone has to fix later.