The fundraising includes commitments from BNP Paribas, Financière Fonds Privés, and existing shareholder, Breed Reply, a leading active operational investor in Internet of Things businesses. The funds will enable METRON to accelerate its international growth, and the further development of its AI-based energy optimisation solutions.
Vincent Sciandra, CEO and Co-founder of METRON, says: “We have seen high levels of customer satisfaction, as customers experience lower than 12 months payback on their investment. I want to thank them for choosing METRON. This capital raise will enable us to change our commercial dimension and to develop our technology. We aim to become a key global player in industrial energy intelligence by 2022.”
METRON offers an energy intelligence platform which collects, aggregates and analyses in real time all types of data generated by industrial systems, while interfacing directly with external data, such as those from energy markets or weather forecasts. The artificial intelligence engine developed by METRON allows manufacturers to effectively reduce their energy consumption and improve their environmental footprint while entering the era of factory 4.0.
Founded in 2013, METRON will have in 2019 a team of around 100 experts, helping manufacturers to maximize value from their energy data and deploy their energy efficiency projects within their production processes. METRON works in all sectors of industrial activities, including mining, steel, paper, glass, chemicals, automotive, food & beverage.
The startup, headquartered in Paris, is active in about ten countries and has six operational centres in Europe, Latin America, Asia and the Middle East. The company decided to make Dubai its regional hub in order to respond to the region’s strong industrial potential and growing awareness of energy efficiency issues.
The METRON-EVA® Factory (Energy Virtual Assistant) platform provides real-time mapping of all energy flows and visual management of energy performance indicators. Through machine learning algorithms and dedicated knowledge bases, it allow s companies to identify in industrial processes, non-intuitive optimization levers and to support their implementation to generate the expected gains. By interfacing directly with energy markets or decentralized energy assets such as renewable energies, factory operations can be optimized in real time according to production and market context.