Emerald AI is responding to an increasingly urgent issue: the rising power demand from AI data centers is outpacing the capabilities of current grid infrastructure
In sum, what to know:
Software turns AI data centers into grid assets – Emerald AI’s Conductor software adjusts compute workloads in real time to reduce energy use during grid stress, offering a path around 7–10 year interconnection delays.
High-profile backers and $24.5M seed – Investors include Radical Ventures, NVentures and individuals like John Kerry, Jeff Dean and Fei-Fei Li, signaling broad interest in solving AI’s energy bottleneck.
Successful demo proves viability – In Arizona, the platform reduced power use by 25% for 3 hours during peak demand while maintaining AI workload performance, in partnership with Nvidia, Oracle and Salt River Project.
Emerald AI has officially launched, announcing $24.5 million in seed funding and revealing the results of its first commercial demonstration.
In a release, the company noted its software platform aims to address the growing energy challenge posed by artificial intelligence (AI) data centers.
The funding round was led by Radical Ventures with participation from Nvidia’s venture arm NVentures, AMPLO, CRV and Neotribe. A number of prominent individual investors have also backed the company, including Google chief scientist Jeff Dean, former U.S. Secretary of State John Kerry and former Australian Prime Minister Malcolm Turnbull, among others.
Emerald AI is responding to an increasingly urgent issue: the rising power demand from AI data centers is outpacing the capabilities of current grid infrastructure. According to industry projections, U.S. data centers could require an additional 50–100 gigawatts of electricity by 2030. However, long interconnection delays and limited capacity threaten to slow AI development and raise energy costs.
“We’re at a critical inflection point as exponential growth of AI computing pressures our electrical infrastructure,” said Emerald AI founder and CEO Varun Sivaram. “To unshackle AI technology progress from power constraints, Emerald AI transforms data centers from grid liabilities into flexible assets.”
The company’s core offering is its Conductor software, which enables real-time orchestration of AI workloads to reduce energy consumption without compromising performance. By making data centers responsive to grid signals, the firm’s software allows operators to navigate long grid interconnection wait times, some of which exceed 7–10 years.
Emerald AI also demonstrated its technology as part of the Electric Power Research Institute’s (EPRI) DCFlex initiative in Phoenix, Arizona. In partnership with Oracle Cloud Infrastructure, Nvidia, Salt River Project and EPRI, the demonstration showed a GPU-based AI cluster reducing its energy use by 25% over a three-hour window during peak summer demand, while maintaining service levels.
On May 3, a hot day in Phoenix with high air-conditioning demand, SRP’s system experienced peak demand at 6 PM. During the test, the data center cluster reduced consumption gradually with a 15-minute ramp down, maintained the 25% power reduction over three hours, then ramped back up without exceeding its original baseline consumption, Nvidia explained in a separate post.
Nivia also noted that Emerald AI achieved this by orchestrating the host of different workloads that AI factories run. Some jobs can be paused or slowed, like the training or fine-tuning of a large language model for academic research. Others, like inference queries for an AI service used by thousands or even millions of people, can’t be rescheduled, but could be redirected to another data center where the local power grid is less stressed, said Nvidia.
John Kerry, added: “Emerald AI’s software delivers immediate impact that unlocks further AI innovation while best utilizing today’s electricity resources.”
Emerald AI is also part of the Nvidia Inception program and counts support from several industry leaders, including BCG chairman Rich Lesser, Google chief sustainability officer Kate Brandt and Galvanize co-chair Tom Steyer.
Looking ahead, Emerald AI said it is preparing for larger-scale implementations of its platform in Phoenix and other locations across the U.S.
