The water industry is under pressure to do more with less - ageing assets, rising compliance demands, stretched workforces, and increasing expectations from regulators and communities. At the same time, vast amounts of data are collected every day but rarely put to work.Water Intel AI helps the water industry turn this untapped data into practical intelligence. By combining equipment monitoring with process optimisation, we support operators, engineers, and managers in making faster, smarter decisions that improve reliability, reduce costs, and build trust in every drop delivered.
Water utilities everywhere are under pressure to keep services reliable and affordable while managing risks and compliance
Ageing assets - pumps, motors, blowers, and treatment equipment past design life.Operator-intensive processes -coagulation, aeration, and chemical dosing prone to variability.Tighter compliance - stricter quality, safety, and reporting with higher penalties.Workforce strain - retirements rising, fewer skilled replacements coming through.Reactive culture - firefighting issues instead of planning ahead.
Most utilities already gather huge amounts of data from SCADA systems, sensors, lab results, and customer interactions.
Turning Data into Reliable Insights
The reality is that much of this data is unused. At the same time, machine learning and AI have reached the point where they can provide reliable insights from this data, improving operations in practical ways.Two things make the timing right:Proven tools can now be deployed in small, low-cost pilots and then scaled with results measured in months, not years.The aim is not to replace operators but to give them better support, reduce fatigue, and provide earlier warnings so compliance and service reliability are easier to maintain.
Reliability AI combines equipment monitoring with process intelligence to give a full view of both asset health and treatment performance. It works by:Continuously monitoring pumps, motors, blowers, and other critical assets to detect early signs of wear or imbalance.Turning raw plant and network data into insights that operators can act on through clear dashboards, alerts, and natural language queries.Optimising treatment and distribution processes through site-specific machine learning models.
Fine-tuning coagulation dosing in real time, cutting chemical use while maintaining water quality.Optimising blower and pump schedules to reduce energy use without compromising compliance.Detecting patterns that point to likely turbidity, chlorine, or nutrient breaches before they happen.Allowing operators to ask simple questions of their plant data such as “Why did turbidity rise yesterday?” and get clear answers.Triaging customer calls or alarms so staff can focus on the most important issues first.Embedding AI Co-Pilots into everyday tools like Teams, Slack, or field apps to provide guided decision support during operations.
Improved reliability, with fewer unplanned failures and service interruptions.Lower operating costs through reduced energy and chemical consumption and longer asset life.Better compliance, with early warnings and clear, data-backed audit trails.A workforce that is supported by AI tools, reducing alarm fatigue and capturing the expertise of experienced operators.Stronger community trust through consistent, safe, and dependable water delivery.