The problem
Water is managed on averages. A utility plans on last year’s demand, a plant on its permit, a farm on the calendar. Meanwhile the network leaks, a heatwave doubles demand in a district, and the first sign of a burst is a phone call. The data to do better often exists, in flow meters and SCADA logs, but it sits unused.
How it works
Water AI connects to the sensors and systems a water operator already has and turns the readings into three things: a demand forecast per zone that planners can act on, leak and burst signals from night-flow and pressure patterns, and dashboards that show where the water actually goes. For agriculture, the same models drive irrigation schedules from soil, weather and crop data.
It builds on our forecasting work with the Athens water utility and on open research the founder has published.
Where it is today
Water AI is in pilot. We are working with a small number of utilities and agricultural partners to validate the models on their networks. If you manage water at scale and want to be part of the next pilot, get in touch.