IoT Development
Connected Devices That Turn Data Into Decisions.
Most businesses are sitting on untapped operational data in factories, fleets, facilities, and field equipment. We build end-to-end IoT systems - from hardware and firmware to cloud connectivity, data pipelines, and dashboards - that turn that data into decisions.
IoT development services across the full stack
IoT spans hardware, firmware, connectivity, cloud, data, and application. We cover all of it - from architecture and embedded development to dashboards and analytics.
IoT Solution Architecture & Consulting
Before any development begins, we design the right architecture for your use case - device selection, communication protocols, cloud platform, data models, and security framework.
→ Strong early decisions prevent months of rework
Common Use Cases
Embedded Systems & Firmware Development
Custom firmware for microcontrollers and embedded Linux systems using C, C++, and Rust. Low-power optimisation, OTA update mechanisms, watchdog recovery, and hardware abstraction layers.
→ Production-grade device reliability at the edge
Common Use Cases
IoT Cloud Platform Development
Backend systems that ingest, process, store, and act on data from thousands of connected devices - on AWS IoT Core, Azure IoT Hub, Google Cloud IoT, or a custom-built platform.
→ Scales from pilot to thousands of devices
Common Use Cases
Device Connectivity & Protocol Engineering
Integration across MQTT, CoAP, AMQP, HTTP/S, Modbus, BACnet, OPC-UA, BLE, Zigbee, Z-Wave, LoRaWAN, NB-IoT, and LTE-M with gateway and edge-to-cloud architecture.
→ Connects heterogeneous devices reliably
Common Use Cases
Edge Computing & Edge AI
On-device intelligence for latency-sensitive or bandwidth-constrained applications using TensorFlow Lite, ONNX, and OpenVINO - so critical decisions don't depend on cloud round-trips.
→ Decisions happen locally when latency matters
Common Use Cases
IoT Dashboard & Visualisation
Web and mobile dashboards that give operators, managers, and executives live visibility into device status, sensor readings, alerts, and trends.
→ Operational visibility for the people who need it
Common Use Cases
What makes working with us different
IoT projects fail at a higher rate than standard software projects. Here's what we do differently - and why it matters for your team long-term.
We think in full systems, not individual layers
The firmware engineer knows what the cloud architect is building. The data pipeline team understands the sensor sampling rates. IoT failures usually happen at the boundaries between layers - we prevent them by keeping the full picture in mind throughout.
We build for production, not just proof of concept
A PoC that works in a lab is not the same as a system that handles 10,000 devices, intermittent connectivity, firmware update failures, and malformed data packets at 3am. We design for those conditions from the start.
Security is not optional in IoT
Connected devices that aren't secured properly become attack vectors. We implement device identity provisioning, mutual TLS, firmware signing, secure OTA updates, and network micro-segmentation from the first sprint.
We design for the operational reality
Your devices will lose connectivity. Batteries will die. Sensors will return out-of-range values. We design edge caching, store-and-forward mechanisms, anomaly detection, and alert logic for how physical systems actually behave.
We manage hardware complexity honestly
Hardware supply chains, certification requirements (CE, FCC, BIS), lead times, and component availability are real constraints. We surface these early, recommend proven components, and build procurement timelines into our project plans.
Platform decisions that don't lock you in unnecessarily
We recommend managed IoT platforms where they make sense and custom infrastructure where proprietary control or cost justify it. We'll always explain the trade-off clearly and give you the information to make that call yourself.
How we approach an IoT project
IoT projects involve more moving parts than most software projects. Our process reduces risk at each stage before moving to the next - especially when hardware is involved.
Typical PoC timeline
for a focused proof of concept with off-the-shelf hardware
Discovery & Requirements Definition
We start by understanding the physical environment your devices will operate in, the business decisions your data needs to support, connectivity constraints, power requirements, expected device count, and data volume.
- Technical requirements document
- Connectivity analysis
- Device count and data volume projections
Architecture Design
Based on the requirements, we design the full-stack architecture - device hardware selection, firmware approach, communication protocols, cloud platform, data pipeline design, storage strategy, and application layer.
- System architecture diagram
- Protocol selection rationale
- Cloud platform recommendation
- Security architecture
Proof of Concept (PoC)
For new use cases or technically uncertain elements, we build a focused PoC that validates device connectivity, data transmission reliability, and sensor accuracy before committing to full development.
- Working PoC with documented results
- Go/no-go recommendation
- Revised project plan
Full System Development
Parallel development across firmware, cloud backend, data pipeline, and application layer - with weekly integration checkpoints. We use hardware-in-the-loop testing throughout, not just at the end.
- Firmware builds
- Cloud infrastructure
- Data pipelines
- Dashboards
- API documentation
Field Testing & Validation
We test in conditions that approximate the real deployment environment - temperature ranges, connectivity variability, concurrent device counts, data volume spikes, and edge cases like power loss mid-transmission.
- Field test report
- Device certification support
- Performance benchmarks
Deployment & Device Management
Phased rollout starting with a pilot deployment, with monitoring and rollback capability built in. Post-deployment, we set up remote device management - OTA firmware updates, health monitoring, and alerting.
- Deployed production system
- OTA update pipeline
- Device management platform
- Operations runbook
The tools and platforms we work with
We're hardware-agnostic and cloud-agnostic. We recommend the right combination for your use case - not what we happen to have invested in.
Hardware / MCUs
ESP32, STM32, Nordic nRF52, Raspberry Pi, NVIDIA Jetson, and custom PCB coordination for production hardware.
Firmware
C, C++, Rust, MicroPython, FreeRTOS, Zephyr RTOS, and embedded Linux (Yocto, Buildroot) for reliable device software.
Connectivity Protocols
MQTT, CoAP, AMQP, HTTP/S, BLE, Zigbee, LoRaWAN, NB-IoT, Modbus, OPC-UA, and BACnet across industrial and consumer IoT.
IoT Cloud Platforms
AWS IoT Core, Azure IoT Hub, Google Cloud IoT, ThingsBoard, Losant, and custom MQTT brokers (EMQX, HiveMQ).
Edge Computing
AWS Greengrass, Azure IoT Edge, Balena, Docker on embedded Linux, TensorFlow Lite, ONNX Runtime, and OpenVINO.
Data & Time-Series
InfluxDB, TimescaleDB, Apache Kafka, AWS Kinesis, Spark, Flink, Elasticsearch, Grafana, and Apache Superset.
What a well-built IoT system actually delivers
IoT investment is justified by the operational and financial outcomes it produces. Here's what businesses typically gain once a production-grade IoT system is running.
Predictive maintenance & reduced downtime
Sensor data from equipment reveals early signs of failure - vibration patterns, temperature drift, current draw anomalies - before the equipment breaks. Moving to predictive maintenance typically reduces unplanned downtime by 30–50%.
Real-time operational visibility
Managers and operations teams stop relying on manual reports and shift handovers. Live data from the factory floor, fleet, or facility is available to anyone who needs it, from any device, at any time.
Energy & resource cost reduction
Automated monitoring and control of energy consumption, water usage, HVAC, and lighting typically reduces utility costs by 15–35% in commercial and industrial environments - with the data to prove it.
Quality control & compliance
Continuous sensor monitoring of environmental conditions, process parameters, and product quality replaces manual spot checks, reduces defects, and creates the audit trail regulated industries require.
New revenue streams & product differentiation
For companies building connected products, IoT enables subscription revenue from data services, remote monitoring offerings, and differentiated features competitors without connectivity can't match.
Operational scalability
Manual processes that require a person to be physically present don't scale. IoT automation removes the physical constraint and lets operations scale without proportional headcount growth.
Frequently Asked Questions
Let's talk about what you're trying to connect
Whether you have a well-defined IoT project, a rough concept, or an existing system you need to fix or scale - we're happy to have a direct conversation about what it would take to get there.
Typically responds within one business day