IoT Development & Integration

What we build

We design and build IoT solutions that bridge hardware and software, connecting devices, sensors, and physical systems to cloud platforms, dashboards, and AI engines. From industrial IoT to consumer connected products, we handle firmware, connectivity, data ingestion, and intelligent processing end-to-end. If you have physical assets generating data that nobody is using yet, we build the system that makes that data drive real decisions.

01 IoT system architecture and device strategy

02 Embedded firmware and device software development

03 Sensor integration and edge computing

04 IoT cloud platform setup using AWS IoT, Azure IoT, and GCP

05 Real-time data ingestion and processing pipelines

06 AI and ML integration with IoT data streams

07 Remote monitoring and alerting dashboards

08 Over-the-air (OTA) update management

09 IoT security and compliance implementation

How we work

Every iot development and integration engagement follows the same disciplined process. No surprises, no scope creep.

Step 1:  Device and connectivity strategy

We start by mapping your hardware environment, data requirements, and connectivity constraints. We identify the right protocols, edge compute strategy, and cloud architecture before anything is built.

Step 2: Firmware and edge development

We develop or integrate the firmware and edge software that runs on your devices, ensuring reliable data capture and local processing where latency or bandwidth require it.

Step 3: Cloud platform setup and data ingestion

We set up the IoT cloud platform, configure device management, and build the pipelines that ingest, process, and store your device data reliably at scale.

Step 4: AI and analytics integration

We connect your IoT data streams to ML models and analytics systems that turn raw sensor data into actionable intelligence, alerts, and automated responses.

Step 5: Dashboard and monitoring deployment

We build the real-time dashboards and alerting systems your team needs to monitor assets, respond to anomalies, and make data-driven decisions from anywhere.

Technologies we use

We choose the right tool for the job, not the trendiest one.

• AWS IoT Core, Azure IoT Hub, Google Cloud IoT for cloud connectivity

• MQTT, AMQP, CoAP for device communication protocols

• Raspberry Pi, Arduino, ESP32, and custom embedded hardware

• Edge computing with AWS Greengrass and Azure IoT Edge

• Apache Kafka and Kinesis for real-time data streaming

• TimescaleDB and InfluxDB for time-series data storage

• Grafana and custom dashboards for monitoring and visualization

• TensorFlow Lite and ONNX for on-device AI inference

Who this is for

• Industrial and manufacturing businesses with physical assets they are not fully monitoring

• Agriculture, energy, and utilities companies looking to bring real-time intelligence to field operations

• Consumer product companies adding connectivity and smart features to hardware products

• Logistics and supply chain teams who need real-time visibility into assets in transit

• Any business with sensors generating data that is sitting unused or going into spreadsheets

Results you can expect

Predictive maintenance: Catching equipment failures before they happen typically prevents losses that are 5 to 10 times the cost of the IoT system.

Real-time visibility: From one dashboard, see the status of every asset across every site, updated in real time.

Automated alerting: Critical thresholds trigger automatic alerts, removing the need for manual monitoring.

Data-driven optimization: IoT data reveals patterns in operations that are invisible to the naked eye and impossible to act on without it.

You already have the sensors. You already have the data. The only thing missing is the system that makes it useful.