Depth over hype
Real models and benchmarks, not AI-wrapper demos.
About
We're solving robotics' hardest problem
Hardware caught up. Manipulation didn't. GripSim exists to give every robot hand human-level dexterity.
Aligned with NVIDIA's Big Bang of Physical AI
NVIDIA InceptionIsaac LabGR00TJetson ThorOmniverseCosmos
Mission
Make manipulation a solved layer
We believe dexterity should be something robot makers buy, not rebuild. One cross-embodiment brain, available to everyone.
- Cross-embodiment by design
- A data flywheel for all customers
- Open to every robot maker
Values
How we work
A small, technical team with a clear point of view.
Compounding moats
We build assets that get stronger with scale.
Customer-first
We win when your robots ship.
Story
How we got here
1
The blocker
We saw manipulation stall every robot deployment.
2
The wedge
We focused on contact-rich dexterity, the hardest reused part.
3
The flywheel
We built a data engine that compounds per deployment.
4
The stack
We shipped five products around one manipulation brain.
2026
Founded [placeholder]
Physical AI
Our category
Global
Ambition
Team
A technical founding team
Robotics, ML, and systems engineers who have shipped real autonomy. [Bios are placeholders pre-launch.]
- Founder & CEO [placeholder]
- ML/Robotics Lead [placeholder]
- Systems Lead [placeholder]
Backers & advisors
People who believe
“A focused team on the right problem.”
“Manipulation is the unlock for the robot economy.”
“The flywheel thesis is sound.”
About FAQ
Questions
Are you hiring?
Yes — robotics and ML engineers with RL, sim-to-real, and tactile experience.
Where are you based?
[City, country placeholder] with a distributed team.
Do you build robots?
No — we build the manipulation layer for robot makers and operators.
Why GripSim
Built for production robotics
The manipulation layer teams ship with, not a research demo.
Cross-embodiment by design
One policy runs across many grippers and hands — no per-robot rewrite.
Closed-loop with touch
Tactyl predicts slip and force so grasps react before they fail.
Runs on the robot
Reflex executes on Jetson at control-loop latency, with safety limits.
A moat that compounds
Every deployment feeds the shared model through the data flywheel.
Stay in the loop
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