AAA-caliber game AI engine for creating and controlling populations of NPCs in game worlds
GPU-accelerated rigid-body dynamics solver for robot learning
Stage
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Founded
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Based in
US
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Pricing model
Freemium
Open source
Pricing
Solo Developer Plan: Free. Pro Plan: $5,000 per title per year during development. Studio Plan: Custom pricing. Free pro plans available for discussion; free trials available.
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Key features
Coppola authoring tool for non-technical designers and writers to create dialogue and interactions
Pre-configured Archetypes with animation, behavior, dialogue and props ready to use
Deep Unreal Engine 5 integration with MetaHumans, Navmesh, and Behavior Trees support
Multi-agent and multi-modal planning for complex character interactions
Rehearsal text simulation to test dialogue before in-engine execution
Engine-agnostic C++ library with SDKs for Unreal, Unity and Roblox
Scale to hundreds of NPCs active simultaneously or thousands with streaming and LODs
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
End-to-end solution: authoring, planning and execution all integrated in one platform
Go from ideas to playtesting in minutes without requiring programmers
Built by industry veterans with over 75 years combined game development experience
No royalties charged when games ship, only for authoring tool during development
Transparent, inspectable AI that runs locally with no black box or cloud dependency
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