Emerald AI Raises $150 Million for AI Data Center Power Software
Emerald AI has raised $150 million in Series A funding at a $1.05 billion valuation, the company announced in a press release. The round was co led by Energize Capital and DCVC, bringing Emerald AI total funding to more than $220 million.
Emerald AI builds software that lets AI data centers adjust power use based on grid conditions. Its Emerald Conductor platform manages AI computing workloads and onsite energy resources to control a facility power draw during periods of grid strain while maintaining critical AI workloads.
The company said it has completed five commercial demonstrations in Arizona, Illinois, Virginia, Oregon, and London. Its software is now deployed commercially at full data center scale, with customers that include AI companies, data center operators, and electric power utilities.
Investors in the round include NVIDIA, Samsung Ventures, Siemens, Aramco Ventures, Salesforce Ventures, GE Vernova, RWE, JERA Ventures, In-Q-Tel, Radical Ventures, Energy Impact Partners, Lowercarbon Capital, and General Catalyst scout fund. Emerald AI said the new capital will support commercial deployments worldwide.
We hope you enjoyed this article.
Consider subscribing to one of our newsletters like AI Funding Brief, Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from: Funding
More from: Data Centers
Subscribe to AI Funding Brief
Industry analysis
2025 Global Business Services Agenda: Gen AI Takes Center Stage
This industry analysis by The Hackett Group explores the transformative impact of generative artificial intelligence (Gen AI) on global business services (GBS) in 2025. The study highlights the shift from exploration to acceleration of Gen AI initiatives, with 89% of executives advancing these projects to improve customer satisfaction, innovate products, and reduce costs. The report also discusses the challenges and strategies for successful Gen AI adoption, emphasizing the need for a technology-enabled operating model and the importance of reskilling the workforce.
Read more