E Energy (ML case study)

Yes it is true that Machine Learning and AI are built on complex mathematical algorithms, but just as you don’t need to know how a plane flies to go on holiday, you don’t need to understand the maths, just the concept and how you can apply it in your business.

E Energy receives a file from the regulator every two weeks with all the gas and electricity tariffs for all households in the market. The format of the file and the data within some fields is not consistent, has anomalies and has variations month to month. In order for the file to be used by the energy company it needs to analyse and cleanse the data, remove duplicates, correct formatting and then run manual scripts to check the data quality of the file. This process can take up to 3 working days, with significant senior resource required.

We developed an AI/ML model which cleans and reformats the tariff file of gas and electricity suppliers.

We trained our model on existing data sets and now it removes the duplicates and fixes the values within the file and highlights any new anomalies in the data. The output file is 100% accurate and it only takes 55 seconds for the whole process from start to finish, providing significant resource and time efficiencies.

The outcome is an annual saving to the business of over £30,000 per annum and the ability to have senior staff focusing on  value add tasks and not data processing.

If you want to explore the opportunities in your business for Artificial Intelligence and Machine Learning to add value drop us a line in info@imobisoft.co.uk

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