IoT Solutions
Sensors on one end, a live dashboard on the other.
Plenty of firms will build you a dashboard. Fewer will build the layer underneath it — the broker, the gateway, the protocol handling, the reconnection logic that keeps data flowing when a device drops off the network. We build the whole chain, which is the part that decides whether the dashboard is trustworthy.
What the chain looks like
- Sensors and devices — temperature, humidity, pressure, flow, counters, and whatever else you need eyes on.
- Edge gateways — collecting locally so a network outage does not mean lost readings.
- A data layer — MQTT for sensor fleets, Modbus TCP/RTU for industrial equipment.
- Live streaming — WebSockets pushing values to the browser as they arrive, not on a refresh timer.
- Dashboards — interactive charts with per-topic minimum, maximum, and average statistics.
- Storage and history — so today's reading means something against last month's.
Systems we have built
We built an MQTT live dashboard end to end in Go: a publisher simulating sensor readings, a subscriber pulling them from a broker, and a custom lightweight broker so the whole thing runs locally with zero external dependencies. Live data streams to the browser over WebSockets and renders as interactive charts with per-topic statistics.
We also built a Modbus live dashboard as a single static Go binary that polls industrial Modbus TCP/RTU devices, converts raw register data into typed metrics, and streams them live. Each device polls independently in its own goroutine with automatic reconnection — suited to factory floors, solar inverters, HVAC systems, and water treatment monitoring.
Where this tends to be worth it
Anywhere you currently find out about a problem by walking over to look at it, or by hearing about it after the fact. Equipment you need eyes on remotely, facilities across several sites, cold chain and storage conditions, energy and utility consumption, production output you currently count manually.
Connecting it to the rest of your systems
Readings become far more useful once they reach the systems that make decisions. We build ERP and CRM platforms too, so live data can feed stock levels, maintenance scheduling, or customer-facing status without a manual export in between. We have also built full data pipelines — Airflow, Spark, Delta Lake, dbt and PostgreSQL — when the volume justifies it.