The first Physics-Native AI
for Runtime Operations


One physics-native platform, applicable wherever AI interacts with the physical world from edge to cloud. Grounded by 27 governing physics from thermal to fluids, all at 60Hz or faster - deterministic, repeatable, and validated. Everything that Physical AI promised - delivered.

Learn more about Manifold

Physics-native AI for the physical world

Manifold is a groundbreaking State Space world model that calculates physics. Not guessing from patterns, but through the fundamental equations that govern how the physical world actually works. Predictions, optimizations, and activities are validated before action occurs - ensuring reliable, safe, and accurate operations.

Sensor InputFusion EncodingWorld StatePhysics EnginePredictionPhysics ValidationActions
98.9%
Zero-shot accuracy
60Hz
End-to-end control loop
20ms
World state refresh cycle
21
Physics domains
28 day
Prediction horizon

Wherever AI meets the physical world

Physics generalizes in fundamental ways that pattern-recognition inference cannot. The same governing equations apply across materials, domains, and industries. Without re-training, without re-engineering - requiring minimal compute and data resources.

Manufacturing

Battery, concrete, composites, steel, pharma

Robotics

Contact-rich manipulation, deformable materials, fluids

Autonomous Systems

Navigation, terrain physics, spatial intelligence

Spacetech

Satellite data, flood prediction, orbital mechanics

AI Stack Augmentation

Physics layer for LLMs, VLAs, robotics platforms

Scientific Discovery

Route optimization, materials research, engineering

Latest news from Niva

Cover image for WMF Bologna 2026: Niva's physics-native approach to safety underscored in robotics and manufacturing
WMF, Bologna, Manifold, physics-native AI, deterministic, robotics, autonomous systems, safety, edge AI, world model, manufacturing, medical logisticsJune 29, 2026 · News

WMF Bologna 2026: Niva's physics-native approach to safety underscored in robotics and manufacturing

Niva attended We Make Future 2026 in Bologna (24-26 June) and witnessed a Physical AI failure firsthand: a commercial industrial quadruped lost control, deviated from its programmed circuit, and injured a pedestrian. The incident was not an anomaly. It was the predictable result of an architectural pattern the robotics industry has normalized, and visible across the WMF show floor.

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Cover image for Web Summit Vancouver 2026: Niva brings Manifold's runtime physics to cross-industry audience
Web Summit, Vancouver, Manifold, runtime physics, edge AI, robotics, manufacturing, materials discovery, deterministic, world modelMay 13, 2026 · News

Web Summit Vancouver 2026: Niva brings Manifold's runtime physics to cross-industry audience

Niva attended Web Summit Vancouver 2026 (12-14 May), introducing Manifold to a cross-industry audience of founders, investors, and enterprise buyers after a satellite-industry debut at SATShow in March. Conversations clustered around manufacturing, robotics, and materials discovery, with the runtime-versus-design-time distinction and a head-to-head comparison against Physical Intelligence's π0.5 as the recurring anchors.

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Cover image for Closing the coupling chain: Applying Manifold's runtime physics to orbital state prediction
Research, Analysis, Orbital Prediction, Space Situational Awareness, VLEO, LEO, Coupled Physics, Manifold, Apogee, Edge DeploymentApril 19, 2026 · News

Closing the coupling chain: Applying Manifold's runtime physics to orbital state prediction

Object-specific orbital state prediction rests on a physics chain from material exposure through gas-surface interaction to ballistic behavior to orbit realism. The literature supports each link. It does not close the chain as a continuous runtime process. Niva's Manifold platform resolves the chain end-to-end at microsecond solver latency with deterministic commits - a world's first.

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