Simulation Infrastructure
for Physical AI

Antim Labs builds structured simulation environments, datasets, and eval suites for robotics teams training and testing embodied agents.

The Problem

Simulation authoring
is the bottleneck.

Robot learning stacks are scaling quickly, but useful simulation environments are still slow to create.

Manual sim authoring

  • Weeks per environment
  • Limited scenario variation
  • Fragile exports
  • Hard to reproduce failures

Gizmo workflow

01

INPUT

Point cloud · Floorplan · Prompt · Image

02

SCENE

Generated 3D world

03

STRUCTURE

SCALECOLLIDERSARTICULATIONSEMANTICSEVAL TASKS
04

EXPORT

USD · MJCF · SDF

05

EVAL

PASS / FAIL metrics

Meet Gizmo.
Automated sim authoring for robotics.

Turn prompts, images, floorplans, and point clouds into structured simulation environments — with real-world scale, collisions, articulation, semantics, and export-ready geometry.

Launch Gizmo →

Built for modern robotics stacks

  • OpenUSD
  • Isaac Sim
  • MuJoCo / MJCF
  • Omniverse
  • ROS / Gazebo
  • Synthetic sensors
  • Eval manifests