AI-Powered Wastewater Revolution: How StormHarvester is Using Machine Learning to Prevent Urban Flooding and Pollution

In an era where climate change, rapid urbanization, and population growth are placing unprecedented strain on our water infrastructure, one Belfast-based startup is emerging as a technological trailblazer in the fight against urban flooding and wastewater pollution. StormHarvester, co-founded by environmental engineering veteran Brian Moloney, is harnessing the power of artificial intelligence and hyperlocal rainfall forecasting to transform how cities manage their wastewater networks.

From Civil Engineering to AI Innovation: The StormHarvester Origin Story

Brian Moloney’s journey to revolutionizing wastewater management is rooted in decades of hands-on experience. After earning his degree in civil, structural, and environmental engineering from Trinity College Dublin, Moloney spent over 15 years leading major civil engineering projects across Ireland, the UK, and Australia. His work in drainage and flood prevention exposed him to the critical vulnerabilities in traditional wastewater systems—systems that were increasingly failing to cope with modern challenges.

“I saw firsthand how outdated infrastructure was struggling to handle the dual pressures of climate change and urban expansion,” Moloney explains. “There was a clear opportunity to apply data-driven solutions to prevent pollution and flooding before they occur.”

This realization led to the founding of StormHarvester, a company that’s now at the forefront of applying machine learning to environmental engineering challenges.

The Technology: AI That Predicts Before Problems Occur

StormHarvester’s core innovation lies in its ability to predict sewer levels, detect blockages, and optimize wastewater network performance through sophisticated AI algorithms. The system combines machine learning with hyperlocal rainfall forecasting to provide utilities with unprecedented real-time insights into their networks.

“Our approach is fundamentally predictive rather than reactive,” says Moloney, who serves as the company’s CEO. “Traditional wastewater management often means responding to problems after they’ve already caused damage. We’re shifting that paradigm entirely.”

The technology works by analyzing thousands of data points from sensors deployed throughout wastewater networks. These sensors monitor everything from rainfall intensity to sewer levels, flow rates, and pressure changes. The AI system then processes this data to identify patterns, predict potential issues, and alert operators before problems escalate into full-blown crises.

The Evolution of a Game-Changing Solution

StormHarvester’s development followed a methodical path of innovation. Initially, the team focused on understanding the complex relationship between rainfall patterns and drainage network behavior. This foundational work was crucial because urban drainage systems are highly sensitive to precipitation—what happens in one part of a network can have cascading effects throughout the entire system.

“Once we understood these relationships, we shifted our focus to predicting future network performance using historical rainfall datasets,” Moloney recalls. “The real breakthrough came when we invested heavily in machine learning development.”

The company’s CTO, Stevie Gallagher, worked closely with Moloney to develop their breakthrough blockage and anomaly detection system. This innovation proved to be a game-changer, helping StormHarvester win their first major competition against established industry analytics providers for Wessex Water, a major UK utility company.

Product Portfolio: A Comprehensive Approach to Network Management

Since its founding, StormHarvester has developed a suite of products that address various aspects of wastewater network management:

Inflow and Infiltration Detection: Identifies unwanted water entering the system through cracks, illegal connections, or other vulnerabilities.

Blockage Detection: Uses AI to identify developing blockages before they cause overflows or backups.

Pump Station Alerting: Monitors pump performance and predicts failures before they occur.

Rising Main Alerting: Focuses on pressurized sewer mains that are critical but vulnerable components of wastewater networks.

Spill Verification: Confirms whether reported spills are actual incidents requiring response or false alarms.

“Our advanced anomaly detection system analyzes data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions,” Moloney explains. “This proactive real-time monitoring allows utilities to have visibility over their entire network, prevent issues before they escalate, and move from lagging indicators to live insights.”

Impressive Growth and Global Expansion

StormHarvester’s technology has clearly resonated with the market. The company now works with 11 UK wastewater utilities and has deployed “tens of thousands” of sensors globally. Their success has been marked by several significant milestones in recent years.

In the past year alone, StormHarvester doubled its headcount, fueling further expansion and creating exciting opportunities in the global market. The company has deployed more than 270,000 sensors worldwide, demonstrating the scalability and effectiveness of their solution.

Perhaps most notably, in January 2025, StormHarvester announced plans to double its workforce over three years and expand into new countries following a £8.4 million Series A funding round. This substantial investment signals strong confidence in the company’s technology and market potential.

The company’s rapid growth was further validated in December when StormHarvester was named Ireland’s fastest-growing technology company at the annual Deloitte Technology Fast 50 awards. This prestigious ranking, which evaluates Ireland’s 50 fastest-growing tech companies based on revenue growth over a four-year period, underscores the company’s exceptional performance in a competitive market.

The Challenges of Scaling Innovation

Despite the impressive growth trajectory, Moloney acknowledges that rapid scaling presented significant challenges for the StormHarvester team. “As we grew, we hired quickly, introduced more structure and refined processes while trying to keep culture and communication consistent,” he explains. “Balancing fast growth with maintaining alignment was a challenge.”

This candid admission highlights a common struggle for successful startups: maintaining the innovative spirit and agility that fueled initial success while building the organizational structure necessary to support larger operations. StormHarvester’s experience offers valuable lessons for other tech companies navigating similar growth phases.

Looking Ahead: Global Ambitions and Sustainable Growth

Currently, StormHarvester is planning further expansion, with particular focus on entering the US market. The company’s successful move into Australia and New Zealand has demonstrated that their technology can scale sustainably while maintaining cultural integrity and quality standards.

“Our expansion into Australia and New Zealand showed us that we can maintain our innovative edge and company culture even as we grow internationally,” Moloney notes. “We’re now preparing for entry into the US market with confidence in our ability to deliver value to new customers while staying true to our mission.”

The timing appears ideal for StormHarvester’s US expansion. American cities are grappling with aging infrastructure, increasingly severe weather events due to climate change, and growing regulatory pressure to reduce pollution. StormHarvester’s predictive approach could offer significant advantages over traditional reactive maintenance strategies.

The Broader Impact: Beyond Business Success

StormHarvester’s work represents more than just business success—it’s contributing to solving critical environmental challenges. Urban flooding causes billions in damages annually and poses serious public health risks when wastewater systems overflow. By preventing these incidents before they occur, StormHarvester is helping protect communities, ecosystems, and water resources.

The company’s technology also supports sustainability goals by optimizing pump operations, reducing energy consumption, and minimizing the need for emergency response resources. As cities worldwide strive to become more resilient to climate change, solutions like StormHarvester’s will become increasingly essential.

Conclusion: A Model for Climate Tech Innovation

StormHarvester exemplifies how deep domain expertise, combined with cutting-edge AI technology, can create solutions to pressing environmental challenges. Brian Moloney’s journey from civil engineering projects to leading an AI-powered environmental technology company demonstrates the power of applying traditional engineering knowledge to modern technological frameworks.

As climate change continues to stress urban infrastructure and populations grow in vulnerable areas, the need for predictive, data-driven approaches to environmental management will only increase. StormHarvester’s success suggests that the future of infrastructure management lies not in bigger pipes and stronger pumps, but in smarter, AI-enhanced systems that can anticipate and prevent problems before they occur.

The company’s rapid growth, significant funding, and industry recognition position it as a leader in the emerging field of AI-powered environmental engineering. As StormHarvester prepares for its next phase of global expansion, it’s clear that this Belfast-based startup is not just managing wastewater—it’s helping to shape the future of urban resilience in the face of climate change.

Tags

AI wastewater management, machine learning flood prevention, StormHarvester technology, Belfast startup success, climate change infrastructure, predictive maintenance AI, environmental engineering innovation, wastewater network optimization, urban flooding solutions, hyperlocal rainfall forecasting, sustainable water management, Deloitte Fast 50 winner, Series A funding environmental tech, smart city infrastructure, AI sensor networks, blockage detection technology, pump station monitoring, rising main alerting, spill verification AI, inflow infiltration detection

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