Brian Moloney

Brian Moloney did not set out to build a software company. He trained as a civil engineer at Trinity College Dublin, studying a bit of software along the way, then specialised in drainage and hydraulic modeling, which is the maths of how water moves through pipes. When the 2008 recession dried up engineering work in Ireland, he moved to Queensland, Australia, and a couple of months after he arrived the 2011 Queensland floods did roughly 3 billion pounds of damage to the state's infrastructure.

Brian Moloney watched that flood unfold over a month, and the part that stuck with him was that everyone could see the rain coming a day or two out, and still nobody could do anything with that knowledge. As a drainage engineer for the local council, his job was literally to drive around and knock on doors asking people to empty their storm tanks before the next downpour. He had just bought his first iPhone, and the gap between the technology in his pocket and the reactive infrastructure protecting whole cities bothered him enough that he started building, in his garage, a basic internet-connected valve he could open and close remotely, then linked it to a weather forecast. That was the seed of StormHarvester.

StormHarvester sells what Brian Moloney calls predictive control for drainage networks. It pulls hyperlocal rainfall forecasts from several weather providers, layers machine learning on top of the sensors a utility already has in its pipes and pumping stations, and works out, asset by asset, what is normal and what is a genuine problem. His favourite way of explaining it is to ask you to imagine driving across a city tonight with every traffic light switched off, because that, he says, is roughly how blind most sewer networks are today. The result is less drama in the control room: on one deployment the system silenced 95% of a utility's storm-time alarms and left on the 5% that actually mattered. It is one of the clearer examples of where water technology is heading, from hardware to software.

Brian Moloney is unusual in that he argues against his own old trade. Hydraulic models, the detailed simulations he used to build as a consultant, are great for planning, he says, but too slow and too hard to keep calibrated to run a live network minute by minute, where a pump might cycle on after ten minutes and off after five. So StormHarvester uses machine learning on real sensor data instead. With Wessex Water, a large utility in south-west England, the system ran for three months across 3,000 kilometres of sewers and flagged 60 blockages in real time before they turned into pollution, at around 95% alert accuracy. Get the accuracy wrong, he points out, and the maintenance crews stop believing the software the first time they drive out to nothing.

Brian Moloney has turned that idea into one of the standout water-tech stories coming out of Ireland and the UK. StormHarvester is now used by roughly 75% of UK wastewater utilities, it raised a $10.2 million Series A in January 2025 led by Emerald Technology Ventures and YFM Equity Partners, and in late 2025 it topped the Deloitte Technology Fast 50 in Ireland on revenue growth of 2,910% over four years, the first Northern Ireland company to do so in 25 years. For a founder whose whole pitch is that the smart way to run water infrastructure is to stop reacting and start predicting, the trajectory is a decent advert for the thesis.

“Could you imagine driving into your city tonight if there were no traffic lights anywhere? It would be chaos. That is what the drainage networks below our city are right now. There is no smarts, there is no predictive in there.”

Brian Moloney is, at heart, a drainage engineer who got tired of watching infrastructure react to weather it could already see coming, and built the software to do something about it.