Kodama raises $7M to automate forestry equipment
What's the deal? Kodama SystemsDealroom has a profile for this one. Try Dealroom →, a robotics company building physical AI for forestry, has raised $7 million in a seed round co-led by KonvoyDealroom has a profile for this one. Try Dealroom → Ventures and Breakwater VenturesDealroom has a profile for this one. Try Dealroom →. Blue Forest Asset Management, NYA VenturesDealroom has a profile for this one. Try Dealroom →, Breakthrough Energy VenturesDealroom has a profile for this one. Try Dealroom →, Congruent VenturesDealroom has a profile for this one. Try Dealroom →, Dangerous Ventures, and M1C also took part. The round brings total funding to $14 million.
What's the endgame? Kodama retrofits heavy forestry equipment with teleoperation and supervised autonomy, letting machines handle repeatable tasks while skilled operators manage complex work remotely. The pitch addresses a hiring problem: when an operator misses a shift, an expensive machine sits idle. The money will fund wider deployments, deeper equipment-maker partnerships, and continued autonomy development.
Why now? Kodama says it is moving past pilots. Over six months, machines running its technology have moved more than 100,000 tons of timber across the southeastern US.
How it stacks up: The round ranks in the 93rd percentile among all-time US seed rounds in energy — notable less for its size than for the operating traction behind it.
"Kodama's tech stack is not something that can be vibe coded," said chief executive officer and co-founder Merritt Jenkins. "It has to work in harsh environments with high uptime for crews that depend on it every day."
The signal: Investors are backing forestry automation, from Nordic Forestry AutomationDealroom has a profile for this one. Try Dealroom →'s roughly €4.3 million round to Deep ForestryDealroom has a profile for this one. Try Dealroom →'s €3 million for mapping drones. Kodama's distinguishing bet is retrofitting existing machines rather than starting with fully autonomous ones — and this round tests whether that incremental approach can scale in a tough off-road environment.
Read more: smb.state-journal.com
Image credit: Kodama Systems
