Predictive analytics for winners not players




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



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


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


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


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


Our Team

The best and brightest


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]