The OS for
Physical AI Agents.
The same governance, orchestration, and audit trail you trust for enterprise AI, extended to robots, autonomous systems, and edge hardware. Real-world actions need real accountability.
How a single physical action flows through the runtime. Conceptual illustration.
<10ms
Sensor to actuator (design target)
100%
Actions policy-checked
0
Unlogged actions
Air-gap
Offline-ready runtime
Core Capabilities
Built for the Physical World
Physical agents act in irreversible, high-stakes environments. The OS that runs them is designed for that reality, not adapted from it.
Real-Time Agent Runtime
A sense, decide, actuate loop built around a sub-10ms design target. The OS schedules execution with real-time priorities, because physical agents cannot wait.
Policy-Enforced Autonomy
Every actuation is checked against safety rules before it runs. STOP, WARN, REQUIRE_HUMAN, or DEGRADE, at agent, subsystem, or fleet scope.
Edge + Cloud Hybrid
Full autonomy on-device for air-gapped or latency-bound sites. Telemetry and policy sync to the cloud. Fail-safe when the network drops.
Physical AI OS is NOT
Physical AI OS IS
The full picture
Sensors, edge, and cloud working as one system.
Robots, drones, and machines on the floor; the runtime governing them at the edge; dashboards and audit in the cloud.
Use Cases
Where Physical AI OS Runs
From semiconductor fabs to autonomous warehouses. One OS, every physical agent.
Industrial Robotics
Fabs · Assembly · Inspection
- Pick-and-place with real-time vision and force feedback
- Automated optical inspection and defect classification
- ISO 10218 / TS 15066 safety policy enforced before each move
Autonomous Vehicles & AGVs
Warehouses · Logistics
- Fleet orchestration across hundreds of AGVs in real time
- Dynamic path planning with collision-avoidance policy
- Human takeover gates for edge cases and emergencies
Drone Operations
Inspection · Delivery
- Multi-drone missions with geo-fence policy
- Real-time anomaly detection for infrastructure
- Compliance checks before every flight, immutable logs after
Edge AI in Fabs
Process control · Maintenance
- On-machine inference for SPC excursion detection
- Predictive maintenance running at the equipment edge
- Offline-capable, with cloud sync for models and policy
Architecture
Five Layers. One Physical OS.
A clean split between sensing, deciding, governing, and acting, so you can upgrade any layer without touching the others.
Cloud Policy & Telemetry
Model updates · Fleet dashboards · Audit logs
Physical AI OS · Edge Runtime
Orchestration · Safety policy · Memory · Audit
Perception Agents
Vision · LiDAR · IMU · Tactile · Acoustic
Decision & Planning
Path planning · Task allocation · Anomaly detection
Actuator Interface
Motors · Grippers · Valves · Comms
Why Physical AI Needs an OS
Robots Are Agents With Bodies.
The principles that make enterprise AI trustworthy, orchestration, governance, and audit trails, matter even more when agents can move, grip, and act.
Safety is a First-Class Citizen
Physical actions are irreversible. Every actuation passes a safety check before execution, enforced by the OS, not bolted on after.
Tamper-Evident Audit Trail
Every sensor reading, decision, and actuator command is timestamped and cryptographically logged for compliance and forensics.
Human-in-the-Loop for Edge Cases
When confidence is low or stakes are high, the OS escalates to a human with context, options, and a timeout before fallback.
Robots Are Agents With Bodies
The same engine that runs your enterprise agents runs your robots. One governance model, one audit trail, across digital and physical.