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.
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
Advancing Physical AI through groundbreaking research
Research: Adapt the Physics, Not the Weights - Forecasting a Turbulent Flow Through Parameter Drift
Read more
Research: The Recipe Is Not the Part - Recovering Composite Cure-Cycle Margin with Instance-Informed Runtime Physics
Read more
Research: Free Intelligence Economics - Paradigmatic, Technical, and Systemic Shifts in AI Discourse
Read moreLatest news from Niva
FABTECH 2026: Niva participates in AWS Professional Program, anchoring runtime physics-native AI against 'Physical AI' on the show floor
Niva attended FABTECH 2026 in Las Vegas (21-23 October 2026), releasing a new GMAW runtime thermal forecasting demo, participating in the American Welding Society (AWS) Professional Program, and observing how ‘Physical AI’ is represented commercially. The term, as deployed by vendors ranging from startups to major robotics manufacturers, covers a vast array of capabilities, though often built on the same foundations. Manifold’s physics-native, deterministic, coupled multi-physics approach anchors a different architectural class.
Read more
Demo: GMAW Welding, per-weldment pass optimization with runtime thermal forecasting
Manifold forecasts each weldment's interior thermal state from arc history and times the next pass per-weldment. In the demo scenario, two parts share a surface pyrometer reading at pass 5; Manifold holds the stop-and-restart part 90 seconds and clears both under the 204 °C limit while the nominal part proceeds. Try it on the Demos page.
Read more
CAMX 2026: Niva releases runtime cure control study and demo for composite manufacturers
Niva attended the Composites and Advanced Materials Expo (CAMX) show in Atlanta (21-24 September 2026), presenting a new technical study and interactive demo on composite cure-cycle optimization. Manifold recovered 92.9% of the margin in an already-optimized recipe and delivered a 1.5x throughput gain on the manufacturer's published thick-part cycle, with no hardware change. Substantive interactions have generated follow-ups across simulation, tier-1 fabrication, materials, and research partners.
Read more