Firmware, Sensors, and the Systems Behind Them
Sensors, firmware, and the dashboard, all built by one team.
What we build
Firmware you can update remotely
Devices ship with the ability to update safely from anywhere, with a way to roll back if something goes wrong. Adding this after the fact is difficult, sometimes impossible, so we build it in from day one, even for the first version.
Telemetry you can trust
Every reading is timestamped the moment it is captured, stored safely if the network drops, and delivered without silently losing data. A dashboard that quietly fills in missing data is worse than one that honestly shows a gap, because someone will make a decision on what they see.
The whole path, one team
From the sensor, to the device, to the database, to the screen someone actually reads, it is all one system built by one team. Splitting this between a firmware contractor and a separate web agency leaves a gap nobody owns, which is usually where these projects go wrong.
Questions on this work
Can you take a project from the sensor all the way to the dashboard?
Yes, and that is exactly why it is worth doing as one project. Most failures do not happen inside the firmware or inside the dashboard, they happen at the gap between them: assumptions nobody wrote down, mismatched timestamps, or unclear rules for handling dropped data. One team covering the whole path removes that gap entirely.
Do you work with existing hardware or only new builds?
Both, though working with equipment you already own is more common. Most older industrial machines still use a documented way of communicating, even if that documentation is an old scanned PDF and the original vendor is long gone. If a protocol truly has no documentation, we say so upfront, since figuring it out takes real time and should be your decision, not a surprise.
How do you handle devices that lose connectivity?
The device stores readings locally and sends them once the connection comes back, timestamped for when they actually happened, not when they arrive. Any gap in the data stays visible as a gap. The alternative, quietly smoothing over a two-hour outage, only leads someone to make a decision based on data that was never collected.