The manipulation layer for robots
4.8 Avg Rating · Trusted by robotics builders

Human-level grasping for any robot hand

GripSim gives any gripper or hand reliable grasping and in-hand reorientation. One cross-embodiment model, trained on a data flywheel, that gets smarter with every grasp.

Built on the NVIDIA Physical AI stack

NVIDIA InceptionIsaac LabGR00TJetson ThorOmniverseCosmos
Why GripSim

Everything a robot needs to grasp

Hardware stopped being the bottleneck. Manipulation is. We ship the layer that fixes it.

One model, many hands

A single cross-embodiment policy runs across grippers and humanoid hands.

Touch + vision

Tactyl predicts slip and force before the robot commits to a grasp.

Closed-loop control

Reactive, in-hand control instead of brittle open-loop scripts.

Source-grade integration

Drop-in policy, runtime, and skill API for your robot stack.

100+ object types

Trained on deformable, occluded, and novel objects in simulation.

Experts standing by

Robotics engineers help you pilot, fine-tune, and ship.

4.8 average rating
Trusted by robotics teams building the future
NVIDIA Inception aligned
What's new

A data flywheel competitors can't clone

Every deployed hand logs real contact data that sharpens the shared policy. Each new customer starts ahead of the last.

  • Cross-embodiment dataset that compounds
  • Morphology-transfer to new grippers fast
  • Sim-to-real bootstrapped by Simdex
How it works

From hardware to dexterity in four steps

1

Connect your hand

Register your gripper or hand and its sensors with Dextra.

2

Fine-tune

Adapt the pretrained policy to your cell with a small dataset.

3

Deploy to the edge

Reflex runs the policy on Jetson at control-loop latency.

4

Sequence tasks

Sequa chains grasps into full jobs and recovers on failure.

Build anything

From bin-picking to humanoid hands

Start where the payoff is daily — warehouse picking and machine tending — then expand to humanoid, service, and medical manipulation.

  • Warehouse pick-and-place
  • Machine tending
  • Humanoid manipulation
  • Service & medical
The GripSim stack

Five products, one manipulation brain

Each product is a component of the same idea — the manipulation layer for robots.

Dextra logo

Dextra

Cross-embodiment VLA manipulation foundation model + fine-tuning toolkit.

Part of the GripSim stack Explore →
Tactyl logo

Tactyl

Tactile-and-vision contact world model that predicts grasp outcomes.

Part of the GripSim stack Explore →
Reflex logo

Reflex

On-robot edge runtime for low-latency closed-loop manipulation.

Part of the GripSim stack Explore →
Simdex logo

Simdex

Domain-randomized manipulation simulation + data-generation engine.

Part of the GripSim stack Explore →
Sequa logo

Sequa

Agentic skill API that sequences and recovers grasps into tasks.

Part of the GripSim stack Explore →
200k+
Grasp episodes simulated (target)
50k+
Object variations in training
4.8
Average customer rating
From the field

What robotics teams say

“Manipulation was our blocker for two years. GripSim gave us a policy that just works across our grippers.”
Lead Robotics Engineer
Logistics integrator [placeholder]
“The data flywheel is the real moat. Every cell we add makes the next one easier.”
VP Engineering
Humanoid OEM [placeholder]
“Reflex on Jetson hit our cycle-time budget on the first try.”
Controls Lead
Manufacturer [placeholder]
Questions

Frequently asked

Do you build robots?
No. We build the manipulation layer — model, runtime, and skill API — for the robots you already build or operate.
Which hands are supported?
Dextra is cross-embodiment and supports many gripper and hand morphologies; new hands are added via morphology-transfer adapters.
Does it run on the robot?
Yes. Reflex runs the policy on NVIDIA Jetson at control-loop latency, with fleet OTA updates.
How do you train without lots of real data?
Simdex generates domain-randomized contact-rich data in NVIDIA Isaac Sim, then the flywheel adds real data per deployment.
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

Manipulation research, in your inbox

Benchmarks, sim-to-real notes, and product updates. No hype, no spam.

Start building your robot's hands today

Give any hand human-level dexterity. Start free or talk to our engineers.