

Custom data analysis results and bespoke turnkey applications for maximising knowledge from your water sector datasets. With a highly experienced and agile approach, every project is tailored to the client optimising on both time and price. Combining both academic rigour and expertise, with real world industry project delivery experience, we are in a unique position to cater to your requirements.
Machine Learning, Data Analytics and Artificial Intelligence applications for the water sector

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Machine learning
HydroInformatics
Hydroinformatics is concerned with the development and application of mathematical modelling, information technology, data science and computational intelligence tools to hydrological problems.
We specialise in data mining and knowledge discovery as well as data analytics (e.g. prediction and classification applications and case studies).
Machine learning employs algorithms to enable computers to find connections (correlations) between data and the patterns we are trying to predict from it (supervised learning) or trying to extract when the outcome is not observed (unsupervised learning).
Generative AI

Generative AI can turn large volumes of technical, regulatory and operational information into practical decision support. Mounce Hydrosmart applies generative AI, large language models and advanced retrieval techniques to complex water-sector problems. Our work includes AI assistants and agentic systems designed to bring together technical evidence, regulatory guidance and operational knowledge - helping users reach faster, better-informed decisions.
These approaches are being applied in projects such as ACQUIRE, our AI-enabled approach to water quality incident response. We offer specialist generative AI and decision-support services for the water sector.
Big Data and Deep learning
The availability and affordability of sensing, smart systems, data storage and transmission technologies means water utilities are increasingly able to collect more data than ever before. Deep learning is when such big data intersects with machine learning. These techniques allow the tackling of problems that exceed human understanding. New formulations of deep neural networks allow the direct transition from data to action.



