Service category
3 services
Our Data and IoT practice connects physical devices to operational intelligence. We design the complete data pipeline: firmware and connectivity protocols (MQTT, CoAP, HTTP), cloud ingestion layers, stream processing, persistent storage, and analytics dashboards that surface actionable metrics to operations teams. Each layer is designed for the data volume and latency requirements of the specific application.
We select storage technologies based on data shape and query patterns. Time-series data lands in InfluxDB or TimescaleDB. Event streams run through Apache Kafka or AWS Kinesis. Aggregated analytics go into BigQuery, Redshift, or Snowflake depending on scale. Dashboards are built in Grafana, Metabase, or custom React applications — chosen based on who reads the data and what decisions it needs to support.
Data and IoT projects typically come from manufacturers monitoring production equipment, logistics companies tracking vehicle fleets, energy companies managing distributed assets, or startups building connected consumer products. We scope each engagement around the device count, ingestion rate, and the business decisions the data needs to enable — not around selling a platform larger than the problem requires.
Streaming data pipelines and real-time analytics systems that process high-velocity data and deliver actionable output in milliseconds, not minutes.
End-to-end IoT system development — device firmware, connectivity protocols, cloud ingestion, edge processing, and operational dashboards — from prototype to deployed fleet.
Data infrastructure for organisations that have outgrown relational databases — data lakes, warehouses, and lakehouse architectures that make large datasets queryable and useful.
