Europe's AI Power Fix: The Startups You Haven't Heard Of

Jan de Vries · 2026-09-21

Earlier this year, I wrote about the AI power crisis and argued that coordination now matters more than new capacity. The numbers haven't improved. Research from the International Energy Agency (IEA) shows that global data center electricity demand is projected to roughly double, from 485 TWh in 2025 to around 950 TWh by 2030, and to grow more than four times faster than total electricity demand from all other sectors. Much of the capacity Europe needs already exists but sits unused most of the time. Software that orchestrates existing assets unlocks that headroom years before new lines and substations can. Following the first piece, my colleague Anna Trendewicz and I looked into who is actually building this software in Europe. We found a small group of companies working across the four efficiency layers: grid, facility, compute, and software. ### Grid: Making Existing Capacity Visible Amsterdam's Sympower and Dublin-based GridBeyond have each raised more than $75 million. Both turn data centers and industrial energy users into flexible grid assets by aggregating their demand and bidding it into balancing markets across multiple European countries. Munich's Entrix ranks among Germany's more established battery storage optimizers and trades flexible capacity across day-ahead, intraday, and balancing markets. Finland's Capalo AI runs a virtual power plant that had contracted more than 1 GW of battery storage by the end of 2025 and has since expanded from the Nordics and Baltics into Poland and Bulgaria. London's Piclo operates a flexibility marketplace that connects distributed energy assets with grid operators, and Vienna's enspired automates AI-driven trading of flexible assets across European power spot markets. (Note: Future Energy Ventures is an investor in both Piclo and enspired.) None of these companies started out as a data center specialist. Most built their platforms for industrial and renewable flexibility, which shows how new the AI-specific version of this problem still is. ### Facility: The Physics Layer Darmstadt-based etalytics, a spin-off from TU Darmstadt, optimizes the cooling, heating, and power systems inside a facility. Its etaONE platform combines AI with physics-based digital twins and model predictive control. Operators can either let it adjust set points automatically or approve its recommendations manually. Data center customers include Equinix, Digital Realty, NTT, and Telehouse. NTT Global Data Centers cut cooling energy by 19% with the software, and Telehouse Germany cut cooling electricity by 10.4% at its Frankfurt campus, a site it already considered well optimized. Across its customer base, etalytics reports savings up to 50%. In 2025, M12, Microsoft's venture fund, led an $8.6 million extension that brought its Series A to $17.2 million, and etalytics opened its U.S. business this year. For AI operators, this matters beyond the energy bill. A site with a fixed grid connection can shift every kilowatt it saves on cooling to its IT load, which turns efficiency directly into sellable rack capacity without a new site or new interconnection. Rotterdam's Gradyent works one step beyond the fence line. Its real-time digital twin optimizes district heating networks for energy companies in more than 35 European cities, and it raised $30 million in a Series B in 2025. The platform can route a data center's waste heat into a city's heating grid, where it warms homes instead of being vented. ### Compute: The Recovery Layer Paris-based FlexAI launched in 2024 with a $30.6 million Seed round led by Alpha Intelligence Capital, Elaia, and Heartcore, with Bpifrance participating. Its software places AI training and inference workload across heterogeneous hardware from different vendors and clouds, so customers aren't tied to a single GPU generation. Bristol-based YellowDog schedules workloads across on-premises, hybrid, and multi-cloud environments, optimizing for cost, carbon, and performance. As I look at these companies, I'm reminded of a quote from Alan Kay: "The best way to predict the future is to invent it." These startups are doing exactly that—inventing a more efficient future for AI in Europe.