Emerald AI secured a $150 million Series A round at a $1.05 billion valuation to develop a platform targeting over 100 GW of untapped U.S. grid capacity for AI infrastructure.
Emerald AI has raised $150 million in an oversubscribed Series A financing at a $1.05 billion valuation to scale technology that enables AI data centers to dynamically adjust their electricity consumption based on real-time grid conditions. Energize Capital and DCVC co-led the round, which attracted a broad coalition of strategic and financial investors across the AI, energy, and industrial sectors.
The investor roster includes NVIDIA, Samsung Ventures, Siemens, Aramco Ventures, Salesforce Ventures, GE Vernova, RWE, JERA Ventures, ADVentures, Sabanci Climate Ventures, In-Q-Tel, Radical Ventures, Energy Impact Partners, Lowercarbon Capital, Marunouchi Innovation Partners, Emerson Collective, The Olayan Group, the Temerty Group, John Doerr, Tom Steyer, Earthshot Ventures, Collective Global, and General Catalyst’s scout fund. Emerald AI now counts 12 Fortune Global 500 companies among its investors and Strategic Advisory Board participants.
The financing follows five successful demonstrations of Emerald AI’s technology at commercial data centers, marking the company’s transition from testing into large-scale commercial deployments. Its flagship Emerald Conductor software platform coordinates AI computing workloads with onsite energy resources to dynamically control a data center’s power draw during periods of grid stress. Designed to reduce or shift electricity demand without compromising critical AI operations, the technology challenges the traditional model of data centers as fixed electrical loads. Instead, Emerald AI positions AI infrastructure as a flexible resource capable of responding to fluctuating power availability—a capability that will grow increasingly vital as electricity emerges as a primary bottleneck for new AI infrastructure construction.
Building new transmission, generation, and grid infrastructure typically takes years, yet data center electricity consumption is projected to account for a significant portion of U.S. demand growth through 2030. Emerald AI estimates that deploying flexible-load technology across the AI infrastructure buildout could unlock more than 100 gigawatts of currently untapped capacity on the existing U.S. power grid. The company argues this capacity could become available years ahead of equivalent new generation and transmission projects.
Commercial validation has already begun. Emerald AI completed five demonstrations across Arizona, Illinois, Virginia, Oregon, and London, partnering with NVIDIA, EPRI, Oracle, Nebius, National Grid, and various regional utilities and grid operators. Following these trials, the company advanced to commercial deployment, recently implementing its technology across an entire California data center to demonstrate grid-responsive power flexibility during peak electricity demand.
Emerald AI is also collaborating with Silicon Valley Power on what the companies describe as a first-of-its-kind Flexible Load Interconnection Program. Under this framework, data centers gain expanded grid access in exchange for providing verified, dispatchable flexibility when the electricity system requires relief. Meanwhile, a major deployment is underway in Manassas, Virginia, where Emerald AI is working with Digital Realty and NVIDIA on a nearly 100-megawatt Vera Rubin AI Research Factory. Developed as a power-flexible AI facility and tested alongside EPRI, Dominion, and PJM Interconnection, the project is expected to come online later this year.
Emerald AI now serves clients throughout the AI power ecosystem, including electric utilities, AI developers, and global data center operators, with additional large-scale deployments scheduled for later in 2026. The Series A capital will fund global commercial expansion as the company partners with firms building new AI infrastructure and utilities navigating rapidly rising electricity demand. By positioning software-based load flexibility as a catalyst for faster data center interconnections, Emerald AI aims to bypass years of conventional grid expansion. The approach also enables utilities to manage peak demand by temporarily scaling back flexible computing loads rather than requiring continuous, maximum-capacity availability. For AI companies, this model offers accelerated access to larger power allocations while preserving uninterrupted capacity for mission-critical workloads.
This commercial rollout aligns with growing interest from both technology firms and power providers in leveraging software to synchronize computing demand with available generation.
“We founded Emerald AI on the conviction that the intelligence driving the AI revolution could solve its own greatest bottleneck: power. Our demonstrations around the world proved that data centers can adjust their power use precisely when the grid needs relief, without compromising critical computing workloads. Today that technology runs commercially at full data center scale, and this financing lets us take it everywhere AI is built, so the AI era can accelerate while the grid becomes more reliable and more affordable for the communities it serves.”
Dr. Varun Sivaram, Founder And CEO Of Emerald AI
“The binding constraint on AI is no longer chips or capital; it is power, and software is the fastest way through it. Emerald AI has converted world-class research into commercial deployments faster than any company we have seen in this category, and we are proud to co-lead this round as the team defines how AI infrastructure and the grid grow together.”
John Tough, Managing Partner At Energize Capital
“Emerald AI’s compute workload orchestration platform makes flexibility a permanent feature of how data centers are powered. This turns data centers into grid-responsive assets instead of energy-hogging liabilities, increasing America’s strength in AI, decreasing rises in electrical bills for communities, and protecting the environment. This is deep tech at its best.”
Zachary Bogue, Co-Founder And Managing Partner Of DCVC