→ AI mobile app development services
AI mobile app development services for products that ship to App Store and Play Store
Native iOS, native Android, or cross-platform mobile apps with AI inside. On-device inference when latency or privacy demands it. Cloud inference when capability demands it.
Overview
How we approach this work.
AI mobile app development services from Resser means production-grade native or cross-platform apps with AI inside the product. Not a wrapper around a public chatbot. Not a no-code template. A real app that ships to App Store and Play Store.
We have shipped mobile apps with on-device transcription, on-device summarization, voice-to-action flows, AI search inside the app, AI-driven recommendations, and assistant features that work offline. The hard parts are model size, battery, latency, and per-user cost.
Most agencies that sell 'AI mobile apps' wrap a cloud LLM call and call it a day. We design the split between on-device and cloud so the unit economics work and the user experience stays fast on a phone that is three years old.
What we build
Concrete deliverables.
AI features inside an existing mobile app
Drop a summarizer, transcriber, smart-search, or assistant into the iOS or Android app you already ship.
AI-native mobile products
Brand-new mobile apps where AI is the core feature. Full app, auth, sync, billing, store-ready.
On-device AI features
Whisper.cpp, MediaPipe, Core ML, Llama.cpp on-device. Private by default. Fast on cellular.
Voice and audio AI
Transcription, summarization, real-time voice assistants. iOS Speech, Android SpeechRecognizer, and on-device Whisper.
Cross-platform with React Native or Flutter
When shipping speed across iOS and Android matters more than platform-perfect feel.
Native iOS (Swift) and native Android (Kotlin)
When performance, hardware integration, or platform-specific UX is the requirement.
Stack
What we build with.
Native
Swift + SwiftUI for iOS. Kotlin + Compose for Android. Core ML, Create ML, NNAPI, MLKit, MediaPipe for on-device.
Cross-platform
React Native (Expo, EAS), Flutter. Native modules in Swift / Kotlin when we need to bridge to platform AI APIs.
On-device AI
Whisper.cpp, llama.cpp, MLC, Core ML / ML Compute, GGUF quantized models, MediaPipe vision tasks, OnnxRuntime Mobile.
Cloud AI
Anthropic Claude, OpenAI GPT-4o, Gemini for vision. Streaming via Vercel AI SDK on a Node or Python backend.
Outcomes
What we ship.
Productivity app: on-device transcription dramatically lowered per-user inference cost vs cloud-only baseline, fast even on older devices.
Field-services iOS app: AI search inside the app with cited answers, working offline when connectivity drops.
React Native consumer app: AI-driven onboarding shipped end-to-end, measurable lift in early-user retention.
References with names available after a scoping call.
Related services
Other places this work shows up.
FAQ
Frequently asked.
Should we go native (Swift / Kotlin) or cross-platform (React Native / Flutter)?
Native when performance, hardware integration, or platform-specific UX is the requirement. Cross-platform when shipping speed across iOS and Android matters more. We assess in discovery week and recommend based on your scope, team, and roadmap.
Can the AI run on-device?
Often yes. Transcription, summarization, search, vision tasks, and small classification models run well on modern phones. We use Core ML, MediaPipe, llama.cpp, Whisper.cpp, and GGUF-quantized models depending on what fits. On-device is private by default and removes per-user cloud cost.
How much does an AI mobile app cost?
AI feature added to an existing app: €15,000-€40,000. New cross-platform AI app: €40,000-€100,000. New native AI app on both platforms with on-device features: €60,000-€150,000+. Discovery week gives a defensible number.
Will the app pass App Store and Play Store review?
Yes. We ship apps that pass review. The most common AI-app review pitfall is unclear data use disclosures and missing privacy manifests. We handle both.
Can you work with our existing React Native or Swift codebase?
Yes. Most engagements drop into your existing repo and follow your branch model and review process.
Want to scope this for your project?
Fill the project-estimate form. We reply within one business day with a preliminary scope and a rough budget bracket.