COR-E is a new data intelligence platform dedicated to the European power market.
A smart approach
We process data using the lastest machine-learning (AI) algorithms to produce models and tools for traders and other market participants.
We offer functional, reliable supply/demand modelling and price forecasting across Europe.
A strong team
Combined experience of over 30 years in European Energy markets, across the utility, trading and banking sectors. Specialised model builders comprising meteorologists, data scientists and full-stack developers.

Concept

Global solution

Access to all key market drivers.
Predictive analysis available for main European countries.
Multi-engine, scenarios-based, price simulations.

Ergonomic and fully customisable platform

Adjustable to each customer’s specific needs and requirements.
Customisable user interface for each user profile.

Expertise in wholesale markets

Understanding and live experience of spot and forward markets and associated regulatory frameworks.

Our team

Photo de Emeric
Emeric - Founder

After 15 years trading commodities for various major players, including EDF Trading, JPM and Mercuria, Emeric decided to get actively involved in the data science revolution. Thanks to a smart, dynamic team that combines mathematical, financial and business skills he plans to bring artificial intelligence to the energy markets.

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Robin - Sales and Marketing

Actively involved in European commodity markets since 1999, Robin has had trading and sales experience in a wide range of energy products at Sempra Energy Trading, JP Morgan and BNP Paribas. A subsequent year studying machine-learning inspired him to make the move towards the more technological environment at COR-E.

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Francesca - Full Stack Developer

Having heard about COR-E in the corridor of a coworking space, Francesca was directly intrigued by the idea of joining the innovative team. After completing her studies in Germany and three years work experience, Francesca decided to make her dream come true by living abroad and searching for a new adventure. She found it in being the project manager, database administrator & client advisor of the smart energy startup.

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Thomas - Data Scientist / Meteorologist

Passionate about meteorology and data science, Thomas has found in COR-E the perfect way not only to apply his knowledge by working on renewable energy models, but also to extend his skills by forecasting day-ahead prices. He stays up-to-date with the latest artificial intelligence technologies and events in the energy world in order to outsCOR-E.

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José - Chief Scientific Officer

Over five years of experience in researching mathematics, scientific computing and mathematical modelling has made José particularly passionate about artificial intelligence. Now he applies machine learning to European power markets along with our other data scientists.

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Audrey - Data Scientist / Meteorologist

After learning about weather and the atmosphere, Audrey had no interest in becoming a weather presenter on TV. Data science, especially machine learning, was the way to go in order to improve her technical capacities in modelling and stay behind the scenes. Within the company, Audrey is responsible for the wind and hydrological models. Creating them, enhancing their performance and improving their quality is just everyday work in order to get the best results for price forecasting.

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Léa - UX/UI Designer

After studying architecture and web development, Léa chose COR-E as the lucky beneficiary of her remarkable web design skills. A little self-taught and naturally curious, she continues to alternate her studies with her work at COR-E, where she is responsible for the graphical and ergonomic aspect of the dashboard along with the startup’s global visual identity.

Photo de Emeric
Mathieu - Full Stack Developer

Having a thirst for knowledge, Mathieu joined COR-E in order to learn as much as possible about computer science. Highly curious by nature, he thrives on being responsible for recovering and rapidly transforming data to meet the needs of the team.

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