Build powerful apps for Apple Watch, Wear OS, Fitbit, Garmin, and custom wearables. Real-time health monitoring, biometric data processing, AI coaching, and seamless companion app integration — all from one team.
From watch face design to backend data pipelines — we handle every layer of your wearable technology product, end to end.
Native watchOS apps using SwiftUI and HealthKit — complications, workouts, notifications, Siri shortcuts, ECG integration, and always-on display features.
Jetpack Compose for Wear OS apps with Google Fit integration, offline caching, tile design, heart rate monitoring, and seamless Android companion sync.
Comprehensive fitness platforms tracking workouts, calories, sleep stages, stress, recovery scores, HRV, and AI-generated personalised coaching insights.
HIPAA-compliant clinical wearable apps that stream ECG, blood oxygen, glucose, and vital signs to healthcare providers in real time for remote care management.
Paired iOS and Android companion apps that sync wearable data, provide rich analytics dashboards, push personalised insights, and manage device settings.
Custom wearable device firmware, BLE communication protocols, SDK development for third-party app ecosystems, and hardware-software co-design for OEM clients.
Native-first development for every wearable ecosystem — we don't cut corners with cross-platform hacks that drain batteries and miss platform-specific health APIs.
Native SwiftUI development with full HealthKit access — ECG, blood oxygen, crash detection, fall detection, medications, and Apple Fitness+ integration.
Jetpack Compose for Wear with Google Health Services API, Samsung Health SDK, offline workout tracking, and advanced sensor fusion capabilities.
Fitbit OS clockfaces and companion apps via the Fitbit SDK. Garmin Connect IQ apps in Monkey C with full access to Garmin's advanced running and cycling metrics.
A wearable that only collects data is half an app. We build the AI layer that transforms raw biometrics into actionable health insights, personalised coaching, and early warning systems — the features that drive daily engagement and retention.
On-device ML models analyse workout performance, sleep quality, and recovery metrics to generate daily personalised training plans, recovery recommendations, and goal-setting nudges.
Continuous biometric monitoring with ML models that detect irregular heart rhythms, abnormal SpO₂ drops, stress spikes, and sleep apnoea patterns — alerting users before symptoms escalate.
HRV, sleep, resting heart rate, and activity load are combined into a daily readiness score that predicts injury risk and tells athletes when to push hard and when to recover.
Voice-controlled wearable interactions and gesture recognition for hands-free operation — critical for medical wearables, industrial safety devices, and sports performance use cases.
Accelerometer and gyroscope fusion with ML models to analyse running form, cycling cadence, golf swing, and weight training technique — providing real-time form correction cues.
Deep learning models process overnight sensor data to accurately classify light, deep, and REM sleep stages — matching clinical polysomnography accuracy without the clinical setting.
Building for wearables requires a rare combination of hardware knowledge, health data expertise, and extreme performance optimisation. We have all three.
Every wearable app we build is profiled for power consumption from day one. We use background sensor scheduling, differential sync, and on-device edge inference to maximise battery life.
Health data demands the highest security. We implement end-to-end encryption, on-device data processing where possible, access auditing, and full compliance with HIPAA and GDPR requirements.
Wearables lose connectivity during workouts, in hospitals, and underground. We design offline-first apps that store, process, and batch-sync data seamlessly when connectivity returns.
Pre-built connectors for FHIR R4, HL7, Epic, Cerner, and major EHR systems — enabling wearable data to flow directly into clinical workflows and electronic health records.
For custom hardware clients, we design BLE GATT profiles, implement secure pairing flows, handle firmware OTA updates, and optimise radio duty cycling for multi-year battery life.
We treat the watch app and companion phone app as equally important — same design system, same data model, seamless sync — so the experience feels cohesive across every screen size.
A 5-phase process that accounts for the unique challenges of wearable development — hardware constraints, health data regulations, and ultra-compact UX.
Target platform selection, sensor capability mapping, battery budget planning, and health data regulatory requirements analysis.
Glanceable UI design for 40–49mm watch faces, one-tap interaction patterns, complication design, and companion app architecture.
Platform-native development (Swift for watchOS, Kotlin/Compose for Wear OS) with health API integration and BLE protocol implementation.
Backend time-series data storage, ML model training, on-device inference optimisation, and clinical accuracy validation against reference devices.
App Store and Play Store submission for watch + companion apps, health app review compliance, beta testing with real wearable hardware, and post-launch monitoring.
Wearable technology is transforming how industries monitor, protect, and empower the people they serve.
Common questions about wearable app development answered by our specialist team.
We develop natively for Apple Watch (watchOS), Wear OS (including Samsung Galaxy Watch), Fitbit, Garmin Connect IQ, and custom wearable hardware. For custom devices, we also develop the BLE communication firmware, companion SDK, and cloud data pipeline. We always recommend native development over cross-platform wrappers for wearables due to battery, sensor API, and performance requirements.
We design all health wearable apps with HIPAA compliance built in — including AES-256 encryption at rest and in transit, minimum necessary data collection, audit logging, business associate agreements (BAA) with cloud providers, and a data retention and deletion policy. For clinical-grade applications, we also support FHIR R4 data standards for EHR integration.
Battery life is our top engineering constraint on every wearable project. We profile power consumption from the first sprint, using background sensor sampling schedules, differential data sync (only sending changes), on-device edge ML inference instead of cloud round-trips, display dimming triggers, and Bluetooth LE connection parameter tuning. Most of our apps achieve 20–30% better battery life than the industry average.
Yes. For OEM clients building custom wearable hardware, we develop the complete software stack: BLE GATT firmware profile, device SDK for iOS and Android developers, cloud data ingestion pipeline, and a reference companion app. We have experience with ESP32, nRF52840, and STM32-based wearable platforms, and can support certification (CE/FCC) with documentation support.
Accuracy depends on the underlying hardware sensors and the algorithms applied. For consumer wearables (Apple Watch, Wear OS), we use the platform's validated health APIs — which have FDA-cleared accuracy for heart rate and ECG on supported models. For custom hardware, we validate our signal processing algorithms against clinical-grade reference devices and can achieve medical-grade accuracy for specific metrics with the right sensor hardware.
A single-platform wearable app (e.g., Apple Watch + iOS companion) typically takes 8–14 weeks. Multi-platform (Apple Watch + Wear OS + backend + web dashboard) takes 16–24 weeks. Custom hardware projects with BLE firmware add 4–8 weeks. Timeline depends heavily on the number of health metrics, AI/ML components, regulatory requirements, and third-party integrations required.
Whether you're a startup with a new wearable hardware concept or an enterprise adding wearable support to an existing health platform, we have the expertise to ship a world-class product.