IoT Development Services
IoT development is the work of building connected devices and the systems behind them: firmware on the device, edge processing close to the sensor, a connectivity layer that moves data reliably, and a cloud platform that ingests, stores, and acts on it. We design and ship that full stack — from the microcontroller board bring-up to the dashboard your operators use.
What IoT development covers
A working IoT product is four layers that have to agree on protocols, timing, and failure behavior:
- Embedded and firmware. C/C++ on ARM Cortex-M (STM32, nRF52, ESP32), RTOS task scheduling, sensor drivers over I2C/SPI/UART, power budgets for battery devices, and OTA update flows that won’t brick a fleet in the field.
- Edge computing. Pre-processing and inference on Linux gateways (Raspberry Pi CM4, NVIDIA Jetson) so the network only carries decisions, not raw streams. Local buffering when the link drops.
- Connectivity. MQTT and CoAP for constrained links, BLE for short range, LoRaWAN and NB-IoT/LTE-M for long-range low-power, plus TLS and certificate-based device identity end to end.
- IoT platforms. Device provisioning, shadow/twin state, and rules on AWS IoT Core, Azure IoT Hub, or a self-hosted MQTT broker (EMQX, Mosquitto) with a time-series store (TimescaleDB, InfluxDB) behind it.
Our approach
We start with the constraints that actually decide the design: power source, duty cycle, expected fleet size, and how bad it is when a device goes offline. From there we pick the radio and protocol, prototype on a dev board, then move to custom hardware once the firmware behavior is proven. Device provisioning and OTA are designed in from day one, not bolted on — a fleet you can’t update remotely is a fleet you can’t fix.
For IoT app development we build the operator-facing side too: provisioning apps over BLE, real-time dashboards over WebSocket/MQTT, and mobile control apps that degrade gracefully when a device is unreachable.
Use cases
- Industrial IoT. Machine telemetry, predictive maintenance from vibration and current signatures, and Modbus/OPC-UA gateways that bridge legacy PLCs to the cloud.
- Smart home. Matter and Zigbee devices, local-first control that keeps working without internet, and energy monitoring.
- Wearables. Low-power sensor fusion, BLE sync to phones, and firmware that fits the battery budget of a coin cell.
- Healthcare devices. Continuous monitoring with reliable data delivery, audit trails, and designs aware of regulatory and data-handling requirements.
Why work with us
We’re AI-first, and for IoT that means running models where the data is created. We deploy quantized vision and signal-processing models on edge hardware — defect detection on a Jetson at the production line, keyword spotting on an ESP32-S3, anomaly detection on accelerometer streams — so a device can decide locally in milliseconds instead of round-tripping to a server. Computer vision on-device keeps video off the network entirely, which matters for both bandwidth and privacy.
That edge-ML work sits on top of solid embedded fundamentals: we read datasheets, measure real current draw, and test OTA rollbacks before they ship.
Tell us the device, the power source, and the fleet size, and we’ll scope the firmware, connectivity, and cloud platform end to end.