---
title: "MATRIX"
description: "MATRIX builds real-to-sim-to-real pipelines for robotics, starting with SimReady assets for NVIDIA Isaac Sim and MuJoCo."
url: https://matrixsim.ai
---

Simulation infrastructure for physical AI

# Bridging the gap between reality and simulation

SimReady assets and environments for robot policy development

[See SimReady assets](https://matrixsim.ai/solutions/simready-assets)

01 / Why simulation

## In the physical world, mistakes are not cheap.

A bug in software can be patched. A robot that fails on an assembly line, in a warehouse or in a hospital can break equipment and hurt people. Physical AI needs reliability before it ships.

1. **Train where it is safe**  
Simulation lets a robot fail millions of times without consequences, and learn from every one.
2. **Test before you deploy**  
A policy should clear a measured reliability bar in a faithful copy of its workplace before it touches the real one.
3. **Close the sim-to-real gap**  
Simulation only helps when what works there works in reality. That gap is the problem we exist to close.

02 / The pipeline

## Real to sim to real.

Bring the real world into simulation, make it behave like the real world, and send policies back out that work. We are solving it one piece at a time, starting with the assets everything else is built from.

1. _Real_  
### Capture  
Objects and spaces from the real world: photos, scans, CAD.
2. _Sim_  
### Reconstruct  
The deployment site rebuilt in simulation.  
Coming soon
3. _Sim_  
### Make sim-ready  
Assets and scenes with physics, materials and joints.  
We are here
4. _Sim_  
### Evaluate  
Policies tested against reliability benchmarks.  
Coming soon
5. _Real_  
### Deploy  
Policies that transfer, with real-world feedback closing the loop.

03 / Available now

## SimReady assets, made autonomously.

Give us an object, or describe one. Get back a simulation-grade asset with geometry, colliders, mass, inertia, friction, materials and joints, validated before it reaches you.

[How it works](https://matrixsim.ai/solutions/simready-assets)

Chest of drawersRES-003 · OpenUSD · MJCFSim-ready

Realchest\_of\_drawers\_photo.jpg

SimRES-003 · OpenUSD · MJCF

Dimensions

62 × 30 × 70 cm

Mass

17.4 kg, derived

Centre of mass

36 cm above base

Inertia

Full tensor, per body

Rigid bodies

4, fixed base

Joints

3 prismatic, 0–165 mm

Collision

30 convex hulls

Materials

Softwood, steel 304

Grasp regions

3, on the knobs

Tested in

MuJoCo 3.17

04 / Solutions

## Two halves of one pipeline.

**R2S · Real to sim**Bring the place a robot will work into simulation.

[R2SComing soon**Spatial reconstruction** · Rebuild a real site, such as a factory cell or a warehouse aisle, as a simulation you can train and test in.](https://matrixsim.ai/solutions/spatial-reconstruction)

**S2R · Sim to real**Close the gap so what works in sim works in the world.

[S2RLive**SimReady assets** · Objects, or plain-language descriptions of them, turned into simulation-grade assets with geometry, colliders, mass, materials and joints, autonomously.](https://matrixsim.ai/solutions/simready-assets)[S2RComing soon**Scenes** · Complete, physically consistent environments composed from SimReady assets.](https://matrixsim.ai/solutions/scenes)[S2RComing soon**Evaluations** · Benchmarks that a policy must pass in simulation before it is trusted in the real world.](https://matrixsim.ai/solutions/evaluations)

05 / Who it's for

## Built for teams putting robots to work.

If your robot has to learn or be tested in simulation before it is deployed, you need assets that behave like the real thing.

1. **Robot learning teams**  
Train manipulation and navigation policies on objects with real physics, not placeholders.
2. **Simulation engineers**  
Stop hand-building colliders and tuning mass. Drop validated assets straight into Isaac Sim or MuJoCo.
3. **Research labs**  
Build benchmarks and datasets on assets that are consistent, documented and reproducible.
4. **Deployment settings**  
Factories, assembly lines, warehouses, hospitals, homes and labs.

Talk to us

## Tell us what your simulation is missing.

[Book a call](https://cal.com/madhav-chawla/30min)