RoboScore
46.4
Out of 100. Its robots, plus proof from customers and the press.
2 of 6 measures have data
News bonus
0.0
From the last 90 days, up to 15
RoboIndex
46.4
No prior week
Rank change
Not yet on file
Now #951 of 1,342 in All sectors · See the board →
Reforestation Robots You Can Trust
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Claim Namu RoboticsMoney and customers
Raised
Not yet on file
No recorded round
Customers
None
No named customer yet
What the score is made of
How it worksThe score is 65% robots, 30% proof from customers and the press, 5% range of robots. Activity and readiness are shown for context.
Backed by
FUNDING ROUNDS AND CUSTOMERS BY ROBOT
Customers
No deployment evidence on file
A deployment is recorded when a public source names both the customer and the robot, or the maker confirms it. Nothing here counts against Namu Robotics.
In Agricultural, Carbon Robotics, Vitirover and GEA Group have deployment evidence on file.
Add a deployment →Backed by: SOSV (on its portfolio ↗)
Namu Robotics develops autonomous, AI-powered tree planting robots designed to supercharge reforestation efforts. Their robots, named Namu, are terrain-adaptive and aim to address labor shortages, low survival rates, and rugged terrain challenges in tree planting, offering faster planting, higher survival rates, and cost savings. They also provide data visualization and analytics for planting impact.
Active products
1
Company facts
- Legal name
- Namu Robotics Corporation
- HQ
- United States
- Founded
- 2025 · 1 yr
- Website
- namurobotics.ai
Active robots by Namu Robotics
1 shown| # | Category | |||
|---|---|---|---|---|
| 1 | ![]() | Vita 1.0 | Agricultural | — |
Safety reports
We checked the US FDA, NHTSA and OSHA registers. No reports found.
Agricultural buying guides
Industry Knowledge →
Ag Robot Vendor Selection: Pilot Data, Financing Options, and Exit Terms
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Field Constraints That Kill Robot Deployments: Terrain, Weather, Crop Spacing
Slope gradients, seasonal mud windows, crop-row geometry, and end-of-row headland length are the four variables that most reliably predict whether an ag robot d…
