Emerald AI has raised $24.5 million in seed funding with backing from NVentures, Nvidia’s venture capital arm.

The funding round was led by Radical Ventures and included participation from Amplo, CRV, and Neotribe.

The funding will support the development of its Emerald Conductor platform, which, the company claims, could enable data centers to obtain a grid connection significantly more quickly by managing energy consumption through AI.

The system effectively works as a mediator between the grid and data centers, orchestrating AI workloads in real-time, enabling data centers to dynamically adjust their energy consumption and support grid stability while assuring acceptable AI compute performance.

It achieves this by coordinating AI workloads across a network of data centers to meet power grid demands, ensuring full performance of time-sensitive workloads while dynamically reducing the throughput of flexible workloads within acceptable limits.

"We're at a critical inflection point as exponential growth of AI computing pressures our electrical infrastructure," said Emerald AI founder and CEO Dr. Varun Sivaram. "To unshackle AI technology progress from power constraints, Emerald AI transforms data centers from grid liabilities into flexible assets, enabling grid operators to swiftly interconnect AI, bolster reliability and energy security, and more efficiently harness the massive spare capacity on today's grids."

Emerald has already tested the technology and recently released the results of a “first-of-its-kind” demonstration as part of EPRI’s DCFlex Initiative in Phoenix, Arizona.

The project, conducted in conjunction with Oracle, Nvidia, EPRI, and the utility Salt River Project, demonstrated that an AI compute cluster using GPUs in a commercial data center can lower power usage by 25 percent for three hours during times of high grid demand, such as peak summer load events. Emerald claimed that the results were achieved without compromising the performance of AI workloads.

According to a Nvidia blog post, the Emerald Conductor solution's ability to modulate power usage can also be utilized by utilities to avoid rolling blackouts, protect communities from rising utility rates, and support integration of clean energy systems into the grid.

“Renewable energy, which is intermittent and variable, is easier to add to a grid if that grid has lots of shock absorbers that can shift with changes in power supply,” said Ayse Coskun, Emerald AI’s chief scientist and a professor at Boston University. “Data centers can become some of those shock absorbers.”

The company is a member of the Nvidia Inception program for startups and is also backed by Google’s chief sustainability officer, Kate Brandt.

The company is the latest in a line of new firms seeking to utilize AI to better manage how data centers interact with the grid. In May, AI startup GridCARE raised $13.5 million to support its solution that aims to leverage advanced generative AI-based analysis to detect pockets with geographic and temporal capacity on the existing grid, to reduce time-to-power for data centers to 6-12 months.

The month before, PJM Interconnection, the US’ largest grid operator, partnered with Google-backed Tapestry to deploy its AI technology to facilitate faster grid connection timelines for power projects and large load users, like data centers.