Amsterdam-based ClimateTech company Dexter Energy has raised €23 million in a Series C funding round to further scale its AI-powered forecasting and trade optimisation services for renewables and batteries.
The round was led by Alantra’s energy transition fund, Klima, joined by Mirova and with continued support from existing investors, ETF Partners, Newion, and PDENH.
“We’re excited to welcome Klima aboard,” said Luuk Veeken, CEO and Founder of Dexter Energy. “They share our belief that AI is now essential infrastructure for an electricity grid increasingly powered by renewables and storage. This investment enables us to grow our team, expand into new markets, and redefine short-term trading for wind, solar, and battery portfolios. In doing so, we can help more companies get the most out of their clean energy and support them in balancing the grid.”
Founded in 2017, Dexter Energy offers advanced machine learning and optimisation solutions for short-term power trading. By integrating forecasting, automation, and asset management, Dexter looks to help energy providers to maximise the value of their wind, solar, and battery portfolios.
Dexter’s mission is to accelerate the energy transition towards a fully carbon-free power system.
With a presence in nine European countries and a team of 90 professionals specialising in short-term power markets, machine learning, quant trading, data engineering, and energy meteorology, Dexter aims to drive innovation and efficiency across the clean energy sector.
Today, Dexter Energy works with over 80 energy companies, including Centrica Energy, Pure Energie, and Luminus.
With the investment, Dexter will expand its solutions for battery trading, boost its optimisation tools for wind and solar energy, and grow into new European markets.
“Dexter Energy exemplifies the kind of cutting-edge energy tech we seek to invest in at Klima: solutions that combine advanced AI with deep energy market expertise to drive real impact. Their ability to optimise renewable and battery trading in and across multiple complex markets will be critical as Europe scales its clean energy infrastructure“, said Iñigo Echaniz, Partner at Alantra’s Energy Transition fund, Klima.
As renewables rapidly scale across Europe – from around 34% of electricity generation in 2019 to 47% in 2024, and an expected 70% by 2030 (as per Dexter) – clean energy producers are facing growing challenges.
They must compete in a fast-changing market where prices are volatile, weather drives constant fluctuations, and traditional subsidies are no longer the main source of income.
In the Netherlands, for example, renewable producers have seen their revenues drop by more than 30% since 2019, due to price declines caused by cannibalisation and rising balancing costs resulting from forecasting inaccuracies – according to data provided by Dexter.
Dexter’s technology reportedly optimises production across the day-ahead, intraday, and imbalance markets. By leveraging physical flexibility, such as temporarily curtailing production or controlling storage, Dexter’s software delivers automated trading strategies.
“We are excited to partner with Dexter and join the journey with Klima and historic investors. We have been impressed by Dexter’s product and the team’s ability to scale in Europe. This strategic investment reinforces our commitment to advancing technology and energy solutions, while creating valuable synergies with our existing infrastructure portfolio,” added Anne Boulet, Investment Director at Mirova.
With this new investment, Dexter will accelerate the development and rollout of its asset-backed trade optimisation solutions for wind and solar across Europe. Dexter will also use the funding to fast-track the development and deployment of its solutions for battery trade optimisation, initially in the Netherlands and then across key European markets.
Read the orginal article: https://www.eu-startups.com/2025/07/dutch-startup-dexter-energy-raises-e23-million-to-scale-ai-powered-forecasting-and-trade-optimisation-services-for-renewables-and-batteries/
