Moving from words to worlds.
Resolve the data silo crisis and break the $1B barrier with federated infrastructure for the next generation of Physical AI.
The high cost of fragmentation
Current systems in this sector suffer from deep-rooted structural inefficiencies that PrimusNeo is built to resolve.
The Training Barrier
AI training costs have skyrocketed by over 4,300% since 2020, creating a massive barrier to entry for all but the largest frontier labs.
The Silo Crisis
68% of organizations cite data silos as their top concern. Spatial AI is uniquely fragmented across proprietary Lidar, Satellite, and IoT protocols.
Computational Waste
Centralized cloud dependencies force a massive "Coordination Tax" on data movement, slowing down real-time navigation and 3D reasoning.
Why PrimusNeo for this sector
Federated World Models
Physical AI Reasoning
Local-First Spatial Inference
Platform layers tailored for you
AMP Runtime
The operational foundation for real-time digital twins and high-fidelity 3D spatial environments.
NEOS Agreements
Define the rules for AI agency, data privacy, and permissioned access to sensitive spatial datasets.
AZOA Rewards
Incentivize data contributors and GPU providers through cryptographic participation and verifiable contribution tracking.
Fractal Engine
Cross-deployment organizational memory that allows AI agents to learn from federated real-world states.
Autonomous Industrial Campus
A logistics campus uses PrimusNeo to train a local spatial model for 500+ autonomous robots, coordinating movement without relying on centralized cloud latency.
Key Outcomes
- →Eliminated "blind spot" data silos via AMP spatial OS
- →90% reduction in training costs through federated learning
- →Programmatic safety policies enforced via NEOS rules
- →Real-time situational awareness persisted in the Fractal Engine
Ready to transform your operations?
Connect with our team to see how PrimusNeo can be tailored to your specific needs.