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ROLLING & SWIVELING

MATERIALS

FLUIDS

LINKED MECHANISMS

GRANULAR INTERACTION

COOKWARE

ARTICULATED MECHANISMS

INDUSTRIAL ROBOTICS

HINGED ASSEMBLIES

The world layer
for Physical AI

Physics-grounded 3D assets and simulation environments for robot training and evaluation.

3D assets
and environments

Train and test beyond
the limits of the field

Train and evaluate robots in repeatable worlds, with precise control over physics, environments, and edge cases.

01

Capture the real world

Reconstruct the task, objects, and operating conditions from field references.

02

Train & evaluate in sim

Hold the scenario fixed, vary the conditions, and compare policies or software builds.

03

Deploy & capture failures

Use deployment failures to extend the next training and evaluation cycle.

FIELD FAILURES FEED THE NEXT TRAINING & EVALUATION CYCLE

Sim-ready assets built to interact

Every asset shown was created by our world agent,
compressing weeks of manual work into minutes.

Data center rackExploded assembly

Real garden shears reference photograph — Garden shearsReal → simulation

Lysol wipes real product photograph — Lysol wipesReal → simulation

Real screwdriver reference photograph — ScrewdriverReal → simulation

DishwasherDoor · racks · spray arms

KitchenAid toasterLift lever motion

Adjustable desk lampBase · shoulder · elbow · shade

Sharpie S-Gel real product photograph — Sharpie S-GelReal → simulation

Mailer boxClosing sequence

Tuck-top boxClosing sequence

Carrot cuttingMaterial interaction

Pillow deformationDeformable material

Glass tube fractureRobotic interaction

Rigid assemblies, moving joints, deformation, and fracture studies.

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Simulation
environments

Build the environment around the task, from connector-level manipulation to navigation through large scenes.

Data centers

Inspect approach geometry and connector-level manipulation.

Warehouses

Vary layouts and lighting around a logistics task.

Manufacturing

Place robot workcells in an assembly environment.

Drone simulation

Explore aerial navigation through a suburban environment.

Urban environments

Compare a scene across day and night conditions.

Construction

Build outdoor workspaces around deployment tasks.

Household manipulation

Study object interaction in cluttered indoor scenes.

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Real-to-sim
comparisons

Compare real and simulated interactions to examine contact, deformation, and task behavior.

REAL CAPTUREISAAC SIM

Grasp & deformation / Plastic cup

REAL CAPTUREISAAC SIM

Squeeze & dispense / Bottle

Motion & mechanics

Liquid dispensing

Cardboard recovery

Flow through a separate idealized nozzle model.

HELD OPEN

174.9°

Front flap anglet = 6.90 s

Flap anglePlastic rest angle

18.7° springback in the first 5 seconds after release.

Box impacts

Tall carton 20 kg drop

Bonded box 30 kg drop

Automated
evaluation

Build repeatable tests from real-world edge cases and failure recordings.

Reconstruct the case and vary layout, visibility, or task conditions.
Compare builds against task-specific metrics under matched conditions.
Review behavior and retain failures as regression cases.

Hosted inference

01Layout variation

02Lighting & weather

03Perception variation

04Task variation

Bring simulation into your workflow

Custom simulation

Define the robot, task, sensors, and success criteria. We build the environment and simulation workflow around your deployment.

TEXT + IMAGES → SIM-READY ASSETS

Generation API

Submit text or reference images, track generation jobs, and download asset exports. Full scene authoring is available in the Gizmo Editor.

EXPLORE THE API

Antim evaluation prototype showing parallel warehouse scenarios and per-scenario results — PROTOTYPE INTERFACE / DEMO RESULTS

Evaluation platform

An evaluation workflow on Newton with hosted inference, scenario variation, and regression testing.

Let’s build the world
your robot needs.

Tell us what you’re training or testing, and we’ll design the simulation around it.