Electric Plant says its AI model interprets plants’ electrical signals
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Electric Plant, founded by Justin Mast and Lee von Kraus, built Bombadil to interpret the electrical signals running through plant stems and indicate possible needs for water, nutrients and light. The startup says the model was trained over three years and already covers about 125 species, using sensors attached to living tissue beneath the bark; the data is sent over a low-power wireless network for cloud processing.
The company says its sensors cost tens of dollars, compared with thousands of dollars for existing tools, and that only a few per acre are needed for accurate results. Mast claims the system can increase yields while reducing water use by 20% or more. Electric Plant raised $11.2 million in a seed round led by Onto Ventures and Climactic, with participation from other investors.
Why it matters · editorial interpretation
The proposal combines lower-cost sensors and cloud processing to turn plants’ electrical signals into management recommendations, according to Electric Plant. The funding indicates commercial interest in this application, although the claimed productivity and water-saving gains remain company assertions.