Native and cross-platform apps, Bluetooth/Wi-Fi pairing UX, and the admin or fleet dashboards your ops team lives in — built to talk directly to the hardware underneath.
The screen your customer opens every day — fast, reliable, and paired cleanly to the hardware underneath it.
Pulled from our case-study library — same AI/human split shown in full, industry context included.
A wearable captures sleep and physiological signals and uses AI to turn longitudinal data into personalized sleep insights and recommendations.
A modular smart-home hub connects home devices and sensors with local-first voice interaction and automation, reducing dependence on cloud processing.
The platform combines occupancy and environmental sensing across a building to understand space utilization and drive more efficient HVAC operation.
We default to React Native or Flutter unless a feature genuinely needs native (specific BLE behavior, background processing limits) — the goal is one codebase where it's safe, native where it isn't.
Pairing UX design and the trickier failure-mode handling (dropped connections, firmware mismatch, multi-device conflicts) stays with a senior engineer — it's the part that breaks demos if AI-scaffolded alone.
AI scaffolds UI screens, boilerplate and test generation; a senior engineer owns UX decisions and every device-pairing edge case.
Yes — it's typically part of the same engagement as the customer-facing app, since both talk to the same backend and device fleet.
Bare-metal to RTOS, matched to your power and timing budget.
Boards designed for manufacturability, not just the bench.
The interface your customer actually touches, paired to the fleet underneath.
Every service above this one uses this layer somewhere.
