Electric Plant Raises $11.2M to Decode How Plants Communicate

Electric Plant has raised an $11.2 million seed round to build an AI model that reads the electrical signals plants use to signal stress, hunger and thirst. Onto Ventures and Climactic led the round, with participation from Ponderosa, Endeavor Catalyst, Ludlow, Michigan Rise, The Fund, Schox VC and angel investor Dug Song.

The three-year-old startup, co-founded by CEO Justin Mast and neuroscientist Lee von Kraus, has spent that time collecting data to train a large language model called Bombadil. The model interprets microvolt-scale electrical changes inside a plant's stem and relays the plant's needs back to growers.

Mast's entry point was a research paper describing a houseplant wired to a motorized stand. Electrical signals from the plant's tissue drove the stand toward a light source when the plant wanted more illumination.

"I'm like, what the heck?" Mast told TechCrunch. "That was the entry to the rabbit hole for me."

What does the model actually do?

Bombadil can currently interpret electrical signals across roughly 125 plant species, Mast said. The range runs from ferns, redwoods and tomatoes to dahlias.

"This is the most diverse model ever created on biological electrical signals," he said. "No one's ever done anything equivalent to this in the animal world."

That claim has no independent benchmark behind it — it rests entirely on the founders' own description of their work. Mast also conceded the model was trained using the very equipment he criticizes: soil probes, handheld spectroscopes and satellite imagery.

"That technology is sophisticated, but its ability to get at the inside of the plant isn't very sophisticated. Most of that stuff still lags quite a bit behind the real-time needs of the plant," he said.

"We know the model will surpass a lot of that equipment," Mast said. That is a forecast, not a measured result the company has published.

How cheap is the hardware?

Existing monitoring tools typically cost thousands of dollars per unit, Mast said. Electric Plant's sensors sell for "tens of dollars," by his account.

Each sensor is roughly the size of an iPhone folded lengthwise. Installers attach it with stainless steel screws that must penetrate the cambium — the living tissue layer just under the bark — to detect the plant's internal microvolt changes. The sensors relay data to a base station over a low-power wireless network, and Electric Plant says it needs only a couple of sensors per acre for accurate readings.

The per-acre frame matters for buyers: two sensors covering an acre, at tens of dollars each, would put monitoring costs in the low hundreds per acre — a steep drop from equipment priced in the thousands. The company has not disclosed sensor pricing tiers or hardware margins.

Can it deliver on yields and water savings?

Customers receive Bombadil's cloud-based interpretations and can adjust watering or fertilization schedules accordingly. Mast claims the system can boost yields while cutting water use by 20% or more.

That 20% figure is a founder's claim without published trial data or named customers. Mast declined to identify who Electric Plant's initial customers are; he pointed only to imaginable applications in agriculture and forestry.

The founders frame the long-term ambition conservatively. "We're listening more than we're speaking, but listening's the first step," Mast said.

For now, the company has $11.2 million, a 125-species model and no disclosed commercial references — which makes the next round of disclosed results, or customers, the real test of whether plant-to-human translation is a business or a research project.