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AI Mobile Apps
AI-powered mobile applications for iOS and Android built with React Native and Expo. Intelligent features including on-device AI, voice interfaces, recommendation engines, and real-time personalisation baked in from day one.
What's Included
- React Native / Expo Cross-Platform Development
- On-Device AI (Core ML / TensorFlow Lite)
- Voice Interface (Whisper + ElevenLabs)
- AI Recommendation Engine
- Offline-First Architecture
- Real-Time Personalisation
- Push Notification AI Optimisation
- Biometric Authentication
- App Store & Google Play Submission
- Admin Dashboard & CMS
Mobile users have higher expectations than ever. They expect apps that remember their preferences, answer questions instantly, surface relevant content without searching, and get smarter with use. Apps without AI are already losing ground to AI-native competitors who ship the same feature set with half the user friction. The bar for a 'good app' has shifted — an app that does not actively learn from user behaviour feels broken.
We build mobile applications with an AI intelligence layer architected from the first line of code. Using React Native and Expo for cross-platform iOS and Android deployment, we integrate on-device AI via Core ML / TensorFlow Lite for offline inference, cloud AI for complex reasoning, voice interfaces using Whisper and ElevenLabs, and real-time recommendation engines. Every feature we build is benchmarked against the goal: does this reduce user friction or increase time-in-app? If not, it does not ship.
Exactly What You Get
Every AI Mobile Apps project includes these specific deliverables. No vague scope, no hidden extras.
Cross-Platform iOS & Android App
Single React Native / Expo codebase deployed to both App Store and Google Play. 95%+ code sharing with platform-native performance.
AI Feature Integration
Voice interface, intelligent recommendations, AI search, or on-device inference — whichever AI capabilities your app needs, fully integrated and tested.
Backend API & Database
Serverless backend with Supabase or PlanetScale, REST or GraphQL API, authentication, and real-time sync.
Push Notifications & Re-engagement
Personalised push notifications powered by user behaviour data and AI-predicted optimal send times.
Admin Dashboard
Web-based admin panel for content management, user analytics, and AI model configuration — no code required to update the app.
App Store Submission
Full App Store Connect and Google Play Console setup, screenshots, metadata, and submission handled for you.
Pricing Framework
AI mobile app projects range from $15,000 for a focused single-feature AI app to $80,000+ for a full-featured platform with custom recommendation engine, real-time data sync, and admin dashboard. Most client projects land between $25,000 and $50,000 for a polished two-platform app with 3–5 AI features.
Our Process
How we deliver AI Mobile Apps projects from kickoff to launch.
Discovery
Define user journeys, AI feature requirements, and success metrics (retention, session length, conversion).
Design
UX wireframes and high-fidelity Figma designs for all screens. User testing with 5-10 real users before development.
Development
2-week sprint development cycles with working demos at each sprint end.
AI Training & Integration
Train and integrate AI models, run A/B tests on recommendations, validate voice interface accuracy.
QA & Submission
Full device testing, App Store review compliance check, and submission to both stores.
Real Results From Real Clients
Numbers from actual AI Mobile Apps projects we have delivered.
Generic fitness app with no personalisation. 68% of users churned within 7 days. High install cost but poor LTV.
AI recommendation engine added to personalise workout and nutrition plans. Day-7 retention improved from 32% to 61%. Average session length up 4.2 minutes. Revenue per user up 88%.
Paper-based inspection process costing field teams 45 minutes per job in data entry. No offline capability.
AI-powered mobile inspection app with offline-first architecture and voice input. Data entry time cut to 6 minutes. 100% offline operation. Error rate reduced 78%.
Technologies We Use
Frequently Asked Questions
Everything you need to know about our AI Mobile Apps service.
Do you build native apps or cross-platform?
We build cross-platform apps using React Native and Expo. This means one codebase deploys to both iOS and Android, cutting development cost by 40–60% versus native. For 95% of use cases, React Native performance is indistinguishable from native. We recommend pure native only for apps with extreme performance requirements like real-time video processing or AR.
What AI features can a mobile app have?
Common AI features we build into mobile apps include: AI-powered search and recommendations, voice input and commands (using Whisper), text and image recognition, on-device inference for offline AI (TensorFlow Lite), personalized content feeds, predictive notifications, AI chatbot assistant, and automated content generation (text, images).
How long does a mobile app take to build?
A focused app with 5–8 screens and 1–2 AI features takes 8–12 weeks. A full-featured platform with 15+ screens, complex AI integration, and admin dashboard takes 16–24 weeks. We always provide a detailed project timeline after the discovery session.
Do you maintain the app after launch?
Yes. We offer monthly maintenance plans from $499/month covering OS update compatibility, bug fixes, performance monitoring, and minor feature additions. We also offer a dedicated retainer for ongoing feature development.
Can the AI work offline?
Yes. Using on-device AI frameworks like TensorFlow Lite and Core ML, we can run AI inference entirely on the device without a network connection. This is essential for field service apps, healthcare tools, and any app used in low-connectivity environments.
How do you handle data privacy for AI features?
We follow a privacy-first AI architecture: on-device inference for sensitive data, no user data sent to third-party AI APIs without explicit consent, full GDPR and CCPA compliance, and data minimisation by default. We document exactly which data each AI feature processes and where it is stored.
Further Reading
In-depth guides related to AI Mobile Apps.
Related Services
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