AI game generator that turns ideas into playable games without coding
GPU-accelerated rigid-body dynamics solver for robot learning
Stage
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Founded
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Based in
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Pricing model
Freemium
Open source
Pricing
Basic Annual: USD $8.33/month (36,000 Universal AI Credits, valid for 2 months). Pro Annual: USD $16.67/month (74,400 Universal AI Credits, valid for 3 months). Elite Annual: USD $33.33/month (150,000 Universal AI Credits, valid for 4 months). One-time purchased credits available with 3-year expirat
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Key features
Text-to-game creation: describe your game idea and AI generates a playable foundation
Template-based creation with customizable parameters
Asset-driven creation with custom characters and visuals
Real-time collaborative editing in the cloud
Visual logic editor for drag-and-drop gameplay modules
Automatic generation of characters, backgrounds, animations, music, and sound effects
Support for 2D, 3D, and multiplayer games
Automatic video generation and cinematic trailers
Browser-based with no installation required
Full editing control and override of AI-generated content
3.8× PhysX throughput on 20 benchmarks geometric mean
13.0× performance on heterogeneous task mixtures
Per-environment work scheduling for efficiency
Reduced-coordinate articulation dynamics
Differentiable simulation
Rigid-deformable coupling support
Compliant and hydroelastic contact
62% less GPU memory than PhysX at matched batch size
3.90 million environment steps per second peak throughput
What makes it different
Creates fully playable games in minutes, not prototypes
Commercial rights included even with free version
All-in-one platform for games and assets in one workflow
Designed for all skill levels from beginners to professionals
No coding knowledge required to create playable games
Designed for heterogeneous workloads with different robots and tasks simulated together efficiently
Integrated into open-source Newton for seamless adoption without separate physics stack
Supports diverse physical interactions beyond rigid bodies
Enables scaling of diverse robot experience for general-purpose learning