Messy public data in. Clean, machine-readable data out.

DataQuoll is a data platform. We take public data that is scattered across agencies, published in incompatible formats and never designed to be read by software, then we aggregate it, normalise it into one consistent schema, and publish it as a REST API. You integrate once. Data that used to cost weeks of parsing, cleaning and babysitting becomes something you can build on the same afternoon, and the time, money and engineering it used to absorb goes back into whatever you are actually making.

Clean, machine-readable data is the product. Better insights and better-performing systems are what it is for, whether that is a dashboard, an automation, a model or a product of your own.

Our coverage today is Australian emergency and hazard data: fires, floods, storms, rescues, hazmat incidents, earthquakes and satellite-detected hotspots, alongside disaster declarations and live river gauges, from 34 official sources across every state and territory. The archive reaches back to 1840.

Emergency data is also the clearest proof of why the platform exists. Australia has eight separate emergency services, each publishing at a different URL, in a different format, on a different cadence, with a different idea of what a timestamp is. We turned that into one API. The same pattern repeats across public data everywhere, and that is the direction DataQuoll is headed.