Agricultural robotics are not a new phenomenon. We’ve seen systems that pick apples and berries, kill weeds, plant trees, transport produce and more. But while these functions are understood to be the core features of automated systems, the same thing is true here as it is across technology: It’s all about the data. A huge piece of any of these products’ value prop is the amount of actionable information their on-board sensors collect.

In a sense, Orchard Robotics’ system is cutting out the middle man. That’s not to say that there isn’t still a ton of potential value in automating these tasks during labor shortages, but the young startup’s system is lowering the barrier of entry with a sensing module that attaches to existing hardware like tractors and other farm vehicles.

While plenty of farmers are happy to embrace technologies that can potentially increase their yield and fill in roles that have been difficult to keep staffed, fully automated robotic systems can be too cost prohibitive to warrant taking the first step.

As the name suggests, Orchard is starting with a focus on apple crops. The system’s cameras can capture up to 100 images a second, recording information about every tree they pass. Then the Orchard OS software utilizes AI to build maps with the data collected. That includes every bud/fruit spotted on every tree, their distribution and even the hue of the apple.

“Our cameras image trees from bud to bloom to harvest, and use advanced computer vision and machine learning models we’ve developed to collect precise data about hundreds of millions of fruit,” says founder and CEO Charlie Wu. “This is a monumental step forward from traditional methods, which rely on manually collected samples of maybe 100 fruits.”

Mapped out courtesy of on-board GPS, farmers get a fuller picture of their crops’ success rate, down to the location and size of the tree, within a couple of inches. The firm was founded at Cornell University in 2022. Despite its young age, it has already begun testing the technology with farmers. Last season’s field testing has apparently been successful enough to drum up real investor interest.

This week, the Seattle-based firm is announcing a $3.2 million seed round, led by General Catalyst. Humba Ventures, Soma Capital, Correlation Ventures, VU Venture Partners and Genius Ventures also participated in the raise, which follows a previously unannounced pre-seed of $600,000.

Funding will go toward increasing headcount, R&D and accelerating Orchard’s go-to-market efforts.

Agricultural robotics are not a new phenomenon. We’ve seen systems that pick apples and berries, kill weeds, plant trees, transport produce and more. But while these functions are understood to be the core features of automated systems, the same thing is true here as it is across technology: It’s all about the data. A huge piece of any of these products’ value prop is the amount of actionable information their on-board sensors collect.

In a sense, Orchard Robotics’ system is cutting out the middle man. That’s not to say that there isn’t still a ton of potential value in automating these tasks during labor shortages, but the young startup’s system is lowering the barrier of entry with a sensing module that attaches to existing hardware like tractors and other farm vehicles.

While plenty of farmers are happy to embrace technologies that can potentially increase their yield and fill in roles that have been difficult to keep staffed, fully automated robotic systems can be too cost prohibitive to warrant taking the first step.

As the name suggests, Orchard is starting with a focus on apple crops. The system’s cameras can capture up to 100 images a second, recording information about every tree they pass. Then the Orchard OS software utilizes AI to build maps with the data collected. That includes every bud/fruit spotted on every tree, their distribution and even the hue of the apple.

“Our cameras image trees from bud to bloom to harvest, and use advanced computer vision and machine learning models we’ve developed to collect precise data about hundreds of millions of fruit,” says founder and CEO Charlie Wu. “This is a monumental step forward from traditional methods, which rely on manually collected samples of maybe 100 fruits.”

Mapped out courtesy of on-board GPS, farmers get a fuller picture of their crops’ success rate, down to the location and size of the tree, within a couple of inches. The firm was founded at Cornell University in 2022. Despite its young age, it has already begun testing the technology with farmers. Last season’s field testing has apparently been successful enough to drum up real investor interest.

This week, the Seattle-based firm is announcing a $3.2 million seed round, led by General Catalyst. Humba Ventures, Soma Capital, Correlation Ventures, VU Venture Partners and Genius Ventures also participated in the raise, which follows a previously unannounced pre-seed of $600,000.

Funding will go toward increasing headcount, R&D and accelerating Orchard’s go-to-market efforts.