Connected device ecosystems and IoT platform solutions.
Multi-protocol support for MQTT, CoAP, BLE, Zigbee, and LoRaWAN connecting thousands of devices reliably.
Custom platforms on AWS IoT, Azure IoT Hub, or Google Cloud IoT for device management, data ingestion, and analytics.
On-device processing and AI inference at the edge for low-latency decision-making without cloud dependency.
Stream processing pipelines that transform raw sensor data into actionable dashboards and automated alerts.
End-to-end encryption, secure boot, OTA updates, and device authentication to protect your connected ecosystem.
Virtual replicas of physical assets for simulation, monitoring, predictive maintenance, and scenario planning.
In the layer between the device and the decision: pipelines that drop messages under load, dashboards nobody can query, updates that need a site visit. The device is rarely the hard part.
Yes, and that is the usual starting point. The first question is what your devices already record, at what interval, and how long it is kept — that determines which questions can be answered at all.
Data resolution and retention, the edge-versus-cloud split for each use case, and how updates reach deployed devices. Those three shape everything built on top, and changing them later is expensive.