Electric Plant raises $11.2M to decode plant signals with AI

Electric Plant, a startup using AI models to interpret electrical signals from plants, has raised $11.2 million in seed funding. The round was led by Onto Ventures and Climactic, with participation from Ponderosa, Endeavor Catalyst, Ludlow, Michigan Rise, The Fund, Schox VC, and Dug Song. The company plans to use the funding to advance its sensor hardware and its large language model, Bombadil.

Co-founded by Justin Mast and neuroscientist Lee von Kraus, Electric Plant has spent the past three years collecting data to train Bombadil, a large language model designed to interpret the subtle electrical signals flowing through plant stems and relay information about plant needs to growers. The model currently covers about 125 plant species, including ferns, redwoods, tomatoes, and dahlias.

The company's sensors attach to plants using stainless steel screws that penetrate the cambium layer beneath the bark to measure microvolt changes. Data is transmitted over a low-power wireless network to a base station, then interpreted by Bombadil in the cloud. Electric Plant says only a few sensors per acre are needed for accurate results.