Stunning iOS and Android mobile apps integrated with on-device computer vision, offline text classification, and responsive neural engine execution.
From computer vision trackers to lightweight offline speech models.
Mobile apps with real-time on-device camera recognition, object detection, and augmented reality interfaces.
Run machine learning models natively on Apple Neural Engine and Android NPU for offline, private AI features.
Applications with integrated high-accuracy transcription, translation, and localized natural voice synthesis.
Feed algorithm development that monitors on-screen behaviors to suggest posts, items, or actions in real time.
High-performance React Native and Flutter apps using native AI SDK wrappers for both platforms.
Internal employee mobile tools with facial authorization, offline asset classification, and invoice audits.
Every application is benchmarked to guarantee clean performance, battery optimization, and data security.
Highly tuned models compiled specifically for Apple's Neural Engine and Android's NPUs for sub-50ms execution.
Perform complex categorization and processing directly on the device with zero network calls and high data security.
Optimized model sizing and quantization (INT8/FP16) to prevent CPU thermal throttling and heavy battery drain.
Execute lightweight workflows on-device and stream heavy computations to secure cloud GPU clusters asynchronously.
Native layouts showing bounding boxes and real-time overlays rendering fluidly at 60fps / 120fps.
Update local model weights over-the-air without submitting new binary updates to Apple App Store or Google Play.
We analyze target model sizes and benchmark execution speeds on target iOS and Android devices.
Design camera overlays, chat dialog screens, and interactive feeds tailored for smart mobile applications.
Compile models to CoreML / TFLite and write native Swift, Kotlin, or React Native interfaces.
Rigorous testing on 10+ target devices to track CPU load, battery drain curves, and memory leaks.
Metadata alignment, store submissions, configuration of vector indices, and OTA pipelines setup.
Schedule a free strategy call to check latency potential and target models compilation specs.
Deploy CoreML and TensorFlow Lite models optimized specifically for on-device Neural Engine processors.