Turn raw device telemetry into dashboards people actually check.
A fleet of connected devices is only as useful as the data platform behind it. We design ingestion pipelines, time-series storage, and analytics dashboards that turn thousands of sensor readings per minute into clear operational insight — sized to your data volume, from a handful of sensors to a multi-building campus generating data around the clock.
Discuss Your ProjectDashboards refreshed in near real time, not batch reports from yesterday.
Time-series architecture that handles a pilot of ten sensors or a campus of ten thousand.
Threshold and anomaly-based alerts that reach the right team before a small issue becomes a big one.
Data volume, retention requirements, and the decisions the dashboard needs to support.
Ingestion pipeline, storage tier, and schema design sized to actual device throughput.
Pipelines, dashboards, and alerting rules, validated against live device data.
Handover with documentation, or ongoing management as your fleet grows.
IoT & Embedded Systems
Reliable, low-power firmware for the devices your product depends on.
IoT & Embedded Systems
Connect devices, buildings, and legacy systems without a rip-and-replace.
IoT & Embedded Systems
Automate lighting, HVAC, and energy management from a single connected system.
Common questions about our IoT Data Platforms service.
We size the architecture to your actual throughput rather than over-building by default. A pilot with a few dozen sensors might use a managed time-series service; a multi-building campus generating continuous telemetry needs a proper streaming pipeline with Kafka or similar at the ingestion layer. We scope this during the architecture phase, not after something falls over.
Most commonly Grafana for operational, real-time dashboards and Amazon QuickSight or Power BI when the audience needs to blend IoT data with other business data. We choose based on who is looking at the dashboard and what else they need to see alongside it.
Yes — we expose IoT data through a clean API layer or direct database connection so it can feed into whatever BI tooling you already use, rather than living in an isolated silo.
Downsampling of historical data, tiered storage (hot data on fast storage, cold data archived cheaply), and defined retention policies agreed with you up front, so storage costs scale predictably rather than growing unchecked.
Simple threshold alerts (temperature exceeds X), and more sophisticated anomaly detection that flags unusual patterns even when no single reading crosses a hard threshold — useful for catching gradual equipment degradation before it becomes a failure.
Both, depending on your needs. Some clients just need the data platform and plug it into tools their team already uses; others want a custom-branded dashboard or mobile app, which we build through our software development team using this platform as the backend.
Our team will scope your requirements and come back with a clear proposal within 48 hours.