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Emerald AI secures $24.5 million in seed funding to develop software that enables AI data centers to dynamically support electric grid stability. Its Conductor platform reduces power consumption during peak demand without compromising AI performance, as demonstrated in a commercial test with major partners. Backed by investors from NVIDIA, Google, and the U.S. government, the company targets large-scale deployment in the coming year.
AI Is Booming—But the Power Grid Can’t Keep Up
The rise of artificial intelligence is intensifying the pressure on America’s electric infrastructure. New data centers across the U.S. are projected to demand between 50 and 100 gigawatts of additional power by 2030. The availability of power grid interconnections remains limited, with some queue delays stretching up to 7–10 years. This growing gap threatens to stall AI innovation and reduce U.S. competitiveness in the global technology landscape.
The North American grid reliability regulator has warned that rising power demands from AI infrastructure could affect system stability. Meeting these demands through traditional methods would require massive investments in electricity infrastructure, which could drive up energy costs for households and businesses alike.
Emerald AI Steps Into the Spotlight With a $24.5M Backing
Emerald AI officially launched on July 1, 2025, announcing $24.5 million in seed funding. The round was led by Radical Ventures and included participation from NVentures, NVIDIA’s venture capital arm, along with AMPLO, CRV, and Neotribe. The company is also supported by prominent individual investors such as:
- Jeff Dean, Chief Scientist at Google
- John Kerry, former Secretary of State
- Malcolm Turnbull, former Australian Prime Minister
- Professor Fei-Fei Li, a recognized AI researcher
- John Doerr, Chairman of Kleiner Perkins
The funding round signals confidence in the company’s approach to managing AI’s energy demands through software rather than solely through hardware or new grid construction.
Meet the Startup Turning Data Centers from Power Hogs to Grid Allies
Emerald AI focuses on converting energy-intensive AI data centers into active participants in supporting the electric grid. Its software platform, Conductor, is designed to optimize when and how data centers consume electricity based on real-time grid conditions. The goal is to allow grid operators to integrate AI infrastructure more quickly and without compromising energy reliability or performance.
CEO Dr. Varun Sivaram described the mission as enabling AI growth without overwhelming existing grid resources. By treating data centers as dynamic energy consumers, the system can unlock spare grid capacity that often goes unused. The software helps prevent data centers from becoming stress points in the electrical system.
What Makes Emerald AI’s Software Different From the Rest
The Conductor platform enables real-time orchestration of AI workloads, dynamically adjusting power consumption to respond to grid stress. During a recent demonstration in Phoenix, Arizona, conducted in partnership with Oracle Cloud Infrastructure, NVIDIA, the Electric Power Research Institute (EPRI), and the Salt River Project utility, the platform reduced power usage by 25% over a three-hour period. This was achieved during a peak summer load event, without compromising acceptable performance levels for AI tasks.
By controlling when and how GPU clusters operate, the platform helps data centers avoid long grid interconnection delays while still scaling operations. The demonstration was part of EPRI’s DCFlex Initiative and is one of the first of its kind to show direct benefits of real-time energy management in commercial AI environments.
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Why Big Names in Tech and Energy Are Betting on Emerald AI
Emerald AI’s leadership includes individuals with significant expertise across energy, computing, and public policy:
- Dr. Varun Sivaram, former energy executive and U.S. diplomat
- Ayse Coskun, Boston University professor and specialist in high-performance computing
- Shayan Sengupta, former leader at Amazon and Intel with two decades in cloud and AI
- Aroon Vijaykar, former executive at Sunrun and AEE Solar
Advisors and investors include former Secretary of Commerce Gina Raimondo, who stated the platform allows faster AI deployment without straining power systems, and John Doerr, who emphasized its ability to unlock up to 100 GW of unused grid capacity.
Additional support comes from NVIDIA Inception, and investors such as:
- Kate Brandt, Google Chief Sustainability Officer
- Rich Lesser, BCG Chairman
- Tom Steyer, Galvanize Co-Chair
- Lukas Biewald, CEO of Weights and Biases
- Chase Lochmiller, CEO of Crusoe
This broad backing reflects a growing consensus on the urgency of aligning AI development with energy efficiency.
Can Smarter Software Solve the AI Energy Crisis?
The company’s approach highlights a software-first path to balancing AI growth and grid reliability. As AI systems demand more power for training, fine-tuning, and inference, traditional infrastructure expansion may not keep pace. Emerald AI’s solution bypasses this by making the existing grid more responsive and data centers more flexible.
Its ability to operate within current power frameworks while delivering reliable AI performance helps mitigate long-term energy cost increases and enhances national energy security. The concept of treating data centers as grid participants rather than passive energy users introduces a new model for managing digital infrastructure.
From Demonstration to Deployment: What’s Next for Emerald AI
Following its successful demonstration in Phoenix, Emerald AI plans to expand its platform to additional sites across the U.S. in collaboration with utilities and cloud providers. The company aims to establish a new standard in grid-responsive computing within the next 6–12 months.
The combination of real-world validation, deep industry support, and a growing need for scalable AI energy solutions places Emerald AI in a position to contribute to national goals around both AI innovation and grid stability.
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