Camus Energy’s grid orchestration platform uses artificial intelligence and machine learning to fill in grid data gaps and model the future. Today, the company announced additional venture funding that it says will help it expand its customer utility base and grow its tech partner ecosystem.
- The top line: Camus added a $10 million extension, led by Congruent Ventures and Wave Capital, to its Series A funding round. The addition follows a $16 million raise in 2021, and brings Camus’ Series A to just over $25 million.
- The market grounding: Venture funding aimed at adoption of digital climate technology has bagged more than $75 billion in the last five years, as AI has been applied to everything from critical minerals discovery to grid planning. Camus itself has been growing rapidly, and said it has increased its annual recurring revenue by 500% since 2021. Today, the platform serves a wide range of power sector customers, including investor-owned utilities, cooperatives, and community choice aggregators.
- The current take: “This round of funding couldn’t have come at a better time, with federal initiatives and consumer demand putting tremendous pressure on the energy transition within the power sector,” said Camus CEO and co-founder Astrid Atkinson. “Utilities are actively seeking out grid orchestration capabilities to integrate new sources of generation and demand. It’s our job to make that transition as smooth and efficient as possible.”
Camus’ software offers utility customers — which include Duquesne Light Company and Vermont Electric Cooperative, among others — a hub for real-time grid visibility, day-ahead forecasting, and distribution system planning insights. But before they can take advantage of that hub, Atkinson said, most Camus customers need help integrating and organizing data from across their organizations.
“Most utilities have a lot of data, they just don’t know quite how to get it to work, and they don’t necessarily have the software systems that will do that well today,” Atkinson told Latitude Media.
Camus’ data integration approach is somewhat unique in that it brings utility data and customer asset data into the same system for side-by-side visibility, Atkinson said. Once there’s a firm foundation of data, Camus builds models that can do forecasting and fill in data gaps, and ultimately provide a real-time view of current conditions.
Load growth from electric vehicles, data centers, and industrial electrification are top of mind for utilities looking to Camus for assistance, Atkinson said. In fact, dealing with load growth is a key driver of AI use cases for utilities.
“Utilities haven’t seen much load growth in a long time,” she said, which means most utilities don’t have the capabilities to know exactly how it will impact their grid, much less the fine-grained or locational data needed to outline their current or future adoption patterns.
“If you think about what we need on the grid, we need to understand more about where challenges are going to hit,” she added. “Utilities need to be able to better incorporate the data that they’ve already started to collect, to understand what that looks like today and in the future.”
