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Intro


SWHERE

Predictive analytics for winners not players

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Intro


SWHERE

Predictive analytics for winners not players

 

with passion for data we use state-of-the-art predictive analytics techniques such as deep learning to extract full value from the data your customers and assets generate

 

Discover

We start by working closely with your teams to understand your data and where you can make best use of predictive analytics

Build

Having found a opportunity to get stuck into, we demonstrate the value we can bring through a proof-of-concept

Deploy

Once you are convinced, we'll then get our software up and running in your day-to-day decision making so you can start realising the value

win

This discovery allows the winners of tomorrow to make the transition from management by knowledge to management by inquisition

Team


Our Team

The best and brightest

Team


Our Team

The best and brightest


where science meets business

our unique combination of in-depth industry knowledge and second-to-none machine learning capability

allowing you to extract full value from your data with the highest possible accuracy and speed

globally recognised leaders in the field of machine learning

Yee Whye Teh

Professor of Statistical Machine Learning at the University of Oxford

Zoubin Ghahramani

Professor of Information Engineering at the University of Cambridge

complemented with in-depth industry experience in utility and energy sectors

Ernst van Duijn

CEO & Founder

 

and a team of almost 20 data scientists including:

Alessandro Davide Ialongo
MSc Machine Learning, UCL

Esben Sørig
MSc Computational Statistics and Machine Learning, UCL

Heiko Strathmann
PhD, Gatsby Computational Neuroscience Unit

Lloyd Elliott
Postdoctoral Researcher, Oxford

 

Mark van der Wilk
PhD, Cambridge

case examples


case examples



swhere in action

case examples where our software has delivered value to our clients

Wind Power Production

Reduce imbalance costs by predicting intra-day power production - reduced the imbalance costs for on-shore wind farm by more than 50%

Gas Distribution

Double the annual avoided repair costs by optimise the replacement strategy through the prediction of the failure rates of gas pipes

Power Distribution

Predict failure of under-ground cable and overhead line to avoid repair costs by better allocation of replacement budget

Field force optimisation

Reduce the travel time and number of jobs completed per day for a network operator to optimise response times and execution of planned work by predicting timing and location of emergencies 

Energy Retail

Reduce repeat calls and re-directing contacts to lower cost channels by predicting customer contact volumes to optimise the contact channel strategy

Water Retail

Reduce debt provision by predicting debt balance payments and predict next best action to improve collection performance 

contact us


Contact Us

contact us


Contact Us


Interested in working together? Get in touch!

[email protected]

+447860640680