EXPLORE-AI provides a full-fledged set of services for global water utilities based on three main pillars:
EXPLORE-AI's CORE is our cloud-native platform for water and wastewater utilities. It is where the journey towards a digital utility of the future begins.
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We provide a full range of bespoke solutions targeted to water and wastewater utilities to help them become digital utilities of the future, walking with them every step of the way.
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Manage your water and wastewater operations with a comprehensive suite of products covering all domains from customer, operations, incident management, asset management and reporting.
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In our view of the Digital Utility of the Future, there are three main enablers for a digital foundation: a new digital model that leverages agile methodologies, digital capabilities building, and a world class digital engine strategy that combines DevOps and a Digital Twin core. Based on the challenges faced by water companies in the next decade, we believe there are key domains to digitise over the next 10 years:
"Next month, we will release the first module of a blockage prediction model as part of Smart Waste with EXPLORE-AI; this will use data sets and machine learning to build predictive algorithms around blockages and the impact on the customer so that we can be a more proactive business rather than reactive. Longer-term Smart is driving our investment strategy."
"We’re also working with a small data analytics start-up called EXPLORE-AI. We certainly weren’t walking blind before those incidents. We had a lot of data, but we weren’t always tapping into it. If you think about servers and production facilities, there are a lot of operational technologies measuring reservoir levels and so on. There is a system of control on those levels which triggers an alarm when those levels are exceeded. That is a system that continually uses data to predict an issue"
"EXPLORE-AI have been a become a key partner for Thames Water over the last few years. EXPLORE-AI have worked collaboratively with us to create ground-breaking new data science driven capabilities which have won awards and helped us significantly improve business performance. The EXPLORE-AI team have worked alongside us, to challenge and steer us and help us develop our own data science skills."
The utility will use this techology and information on water supply to generate insights and determine appropriate response and boost customer service. It is here that the Explore-AI will be applying some of the data analytics insights and analytical tools.
“We are extremely proud to be doing work for Thames Water,” says Shaun Dippnall, CEO of EXPLORE-AI. “They’re on the cutting edge in digitising their business and it’s an amazing opportunity for us to be working for them.”
EXPLORE-AI was also recently appointed by UK-based insurance group Correlation Risk Partners to apply data science and the latest machine learning techniques to solve some of the difficult problems across their insurance portfolio. Currently Explore-AI is working on three projects across the group.
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We are mostly data engineers and data scientists, with a deep knowledge on how to structure, model, and build predictive algorithms to solve real-life problems.
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We work with agile methodologies, iterating to generate value on fast-paced EXPLORE-AI/customer squads.
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We have spent the last years building a CORE Platform with Digital and Analytical Twins that has paved the way for the deployment of many award-winning solutions in the water industry.
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Over the last few years we have successfully participated in many UK and Global competitions on AI, ML, and Data Science:
We got awarded the IoT App of the year from for our use of acoustic loggers (IoT devices) in the mobile web application. The application displays the acoustic logger information to leakage detection technicians in the field to assist them finding leaks quicker.
We got recognised as highly commended in the category of AI/ML App of the year award for our use of Machine Learning in the leakage detection web application. A machine learning model is used to highlight the highest likelihood leaking pipes in the network that assists the leakage detection technicians finding leaks quicker.
We got recognised as highly commended in the category of AI/ML App of the year award for our use of Machine Learning in the leakage detection web application. A machine learning model is used to highlight the highest likelihood leaking pipes in the network that assists the leakage detection technicians finding leaks quicker.