Kodama raises $7 million to bring robotics to forestry

Kodama Systems said today it has raised $7 million to bring physical AI to forestry. The company said it will use the latest funding to support commercial deployments, deepen OEM partnerships and continue the development of supervised autonomy capabilities for complex off-road environments.

“Right now, we are working with several forestry companies in the southeastern United States,” said Ben Pinfield, a go-to-market associate at Kodama The robot report. “We are at a point where we are growing, integrating into new types of machines and developing greater autonomy capabilities in forestry.”

Kodama technology is already used in commercial logging operations in the southeastern United States. Over the past six months, machines equipped with the company’s technology have moved more than 100,000 tons of lumber in multiple states.

“We focus specifically on timber planting operations,” said Merritt Jenkins, co-founder and CEO of Kodama. “If we look more broadly, though, it’s a land management tool, and it’s absolutely a tool that will be used in fire mitigation, from a forest thinning perspective, as well as fire suppression.”

Including the latest funding, Kodama has raised a total of $14 million to date. Konvoy Ventures and Breakwater Ventures co-led the round. Blue Forest Asset Management, NYA Ventures, Breakthrough Energy Ventures, Congruent Ventures, Dangerous Ventures, M1C and others also participated in the round.

The forestry sector is facing difficult conditions

Forestry contractors face many challenges. Demand for timber, forest management and fire resilience activities is increasing, but each requires long hours on remote construction sites.

“If you’re a potential logger in your 20s and you’re thinking about going into the industry, you need to be on site at 5:30, which means you usually leave the house at 4:00 or 4:30 in the morning,” Jenkins said. “So, you’re on a machine for nine or 10 hours a day, driving over stumps and rocks and ruts, beating your body up all day. There are some loggers we’ve talked to who have worked, say, eight skidder operators in a year. That’s brutal turnover in this industry for this type of operator.”

As fewer people enter the industry and more operators retire, it becomes increasingly difficult to find experienced and reliable operators, and fewer and fewer people want to enter the industry.

“For heavy equipment operations, that [work] it can be pretty hard on their bodies,” Pinfield said. “It’s like the bang isn’t worth it in terms of the physical compromise for a lot of these operators. Therefore, our clients have difficulty hiring talent. Even when they do manage to hire talent, many times, it is unreliable.”

What does Kodama technology do on construction sites?

Kodama combines supervised autonomy with teleoperation, allowing machines to handle repeatable tasks while expert operators remotely handle complex jobs and edge cases. The Sonora, California-based company said this hybrid approach amplifies the capabilities of experienced operators and improves machine utilization.

Kodama said he is currently working with skidders on logging sites.

“When a group of trees are cut down, a logger equipped with a large claw called a grapple picks them up and drags them to the landing where they are then loaded onto trucks. Essentially, it’s moving these trees from one location to another,” Pinfield explained. “The ultimate goal is to also work on the other machines in those fleets, namely the cutter and the loader.”

Kodama said that as more machines are deployed, the benefit from data accrues through a continuous learning cycle across equipment, operators, construction sites and forestry workflows.

“Every day that we use the machine remotely, we generate about a terabyte of training data,” Jenkins said. “Starting two and a half years ago, we took an explicit direction to start with teleoperation and incrementally add autonomy, rather than autonomy first with a teleoperation failover. It was absolutely the right decision. Now the amount of training data we are generating across multiple operational environments in the Southeast is enormous.”

Kodama works directly with existing OEMs

Kodama is building its platform within the existing forestry equipment ecosystem. This allows customers to adopt new operational capabilities while preserving the value of their existing machine fleets. Jenkins said the company is integrated with two of the three largest equipment manufacturers in the world.

“Integration with OEMs is preferable because you can leverage all their knowledge and all the sensors and fault detection already on the machine,” Jenkins said.

Range upgrades are common in the construction world, but these are typically aftermarket kits. Jenkins said that in the construction industry, OEMs like Caterpillar create closed systems, so you can’t work directly with the OEM.

What has Kodama learned from construction sites so far?

Kodama has already deployed its technology to customers in the southeastern United States over the past two years. Pinfield said the company has been working with a client in Georgia for more than a year.

“It’s always a learning process. Every logging site is a little different, with different terrain and a different crew that you have to work with and introduce them to this new technology,” Pinfield said. Among the biggest benefits of automation for these site operators are reliable and consistent operations.

The team also saw improvements in safety thanks to the technology. “Every person I’ve talked to at logging sites tells a crazy story about how they know someone in the cab who flipped their car, or got hurt, or a tree blew away. So, taking them out of the cab and having it controlled remotely or autonomously is much safer,” Pinfield said.

Looking ahead, the company plans to expand deployments and use the data collected to improve productivity on construction sites.

“Right now, there are several people coordinating over CB radio,” Jenkins said. “We know the real-time location of our machines. We have parameters of productivity, fuel consumption, as well as shock and vibration on the machines. Therefore, we believe we can possibly further optimize these sites in terms of how the machines are used and how they coordinate with each other.”