Heron Power, the grid technology startup founded by former Tesla VP of powertrain and energy engineering Drew Baglino, just closed a $140 million funding round to scale production of what the company calls grid-altering technology. The raise comes as data center operators and AI companies scramble to secure reliable power infrastructure, with Baglino bringing his experience building Tesla's battery and energy systems to tackle one of tech's most pressing bottlenecks. According to TechCrunch, the capital will fund construction of a giga-scale manufacturing facility.
Heron Power is betting big on manufacturing scale to solve the electrical grid crisis that's holding back AI expansion and data center growth. The startup, led by former Tesla executive Drew Baglino, just secured $140 million to build what it describes as a giga-scale production facility for grid technology - borrowing the naming convention and production philosophy that made Tesla's battery factories famous.
Baglino left Tesla in 2024 after an 18-year run as senior vice president of powertrain and energy engineering, where he oversaw development of the company's battery systems, drive units, and energy storage products. His departure came during a broader executive shuffle at the EV maker, but the move now looks strategic. He saw an opening in the market that Tesla wasn't pursuing: grid-level power infrastructure specifically designed for the explosive demands of modern data centers and AI compute.
The timing couldn't be better. Tech giants are racing to build data centers to support AI training and inference, but they're hitting a wall - literally running out of available grid capacity in key markets. Microsoft, Google, and Amazon have all acknowledged power constraints as a limiting factor for AI infrastructure expansion. Some are turning to on-site nuclear reactors and other creative solutions, but the fundamental problem remains: the electrical grid wasn't built for the kind of concentrated power demands that modern AI facilities require.












