About
H2OS began with a simple question: why are water systems still so hard to monitor well, even with modern sensors?
The idea came from hands-on work in the Michigan Aquaponics Club at the University of Michigan, where we experienced the limits of remote water quality monitoring firsthand. Data was often delayed, fragmented, and hard to act on. In many cases, operators only recognized a problem after the system had already started to decline.
That gap between monitoring and decision-making became the starting point for H2OS.
Today, H2OS is building an edge AI water intelligence platform for aquaculture. Our system combines industrial sensing, on-device risk prediction, cloud infrastructure, and operator tools to help farms move from reactive monitoring to earlier detection and faster response.
We believe better water systems need more than dashboards. They need intelligence at the edge.
