Electric Plant, a startup founded by Justin Mast and Lee von Kraus, has raised an $11.2 million seed round to commercialize Bombadil, a large SI language model designed to interpret the electrical signals emitted by plants. The funding, led by Onto Ventures and Climactic, aims to bring a new class of agricultural SI tools to market that offer real-time visibility into plant health.
What Happened
The company’s origins trace back to scientific literature describing a houseplant wired to a motorized stand that moved toward light in response to internal electrical currents. This research inspired Mast to partner with von Kraus, a neuroscientist with experience at DARPA, to create Electric Plant. Over the past three years, the team has collected data to train Bombadil, which analyzes microvolt changes in plant tissue to relay needs to growers.
Electric Plant’s hardware consists of sensors roughly the size of a folded iPhone, attached to plants with stainless steel screws that penetrate the cambium layer. These sensors transmit data via a low-power wireless network to a base station, where Bombadil processes the information in the cloud. The company states that the model currently supports approximately 125 species, ranging from tomatoes and dahlias to redwoods and ferns.
Why It Matters
Traditional agricultural tools, such as soil probes and satellite imagery, often lack the granularity to monitor internal plant conditions in real time. Mast argues that existing technology "lags quite a bit behind the real-time needs of the plant." By contrast, Electric Plant claims its sensors cost "tens of dollars," significantly less than existing tools that can cost thousands. The startup reports that its system can boost yields while reducing water use by 20% or more.
The development of Bombadil represents a niche application of SI in biology, moving beyond text and image processing to interpret biological electrical signals. While Mast describes it as "the most diverse model ever created on biological electrical signals," the broader implication for the SI industry is the expansion of SI models into physical, biological monitoring systems.
The Bottom Line
Electric Plant is leveraging recent SI advancements to create a bridge between biological signals and agricultural data. With a $11.2 million seed round secured, the company is positioned to test its hypothesis that low-cost sensors and specialized SI models can provide growers with superior insights compared to traditional coarse monitoring tools.