Resources
Deployment guides.
Technical resources covering assessment, architecture, safety, operations, and economics for physical-AI systems.
Assess Your FacilityWhat Is Physical-AI Deployment?
How AI moves from the cloud into the physical world — robots, cameras, edge systems, and the integration layer that makes it all work.
Cloud, Edge, and Hybrid Robot Intelligence
Where should inference run? Cloud, edge, and hybrid architectures for latency, safety, privacy, and resilience.
External Cameras for Robot Workcells
Why facility-mounted cameras provide better context than onboard vision alone. Calibration, sync, and multi-robot sharing.
How to Assess a Facility for Robotics
The structured approach: workflow, infrastructure, network, safety, economics. What to evaluate before selecting hardware.
From Robot Pilot to Production Deployment
Why most pilots fail to scale. The seven-stage deployment lifecycle that turns a successful demo into a reliable operation.
Safety Boundaries for AI-Controlled Robots
Why local deterministic controls must retain authority. Emergency stops, motion limits, network-loss behavior, and safe states.
Robotics Connectivity and Failure Planning
Latency, jitter, redundancy, and network-loss behavior. Designing connectivity around the task, not the hardware.
Managed Robotics Operations
What happens after deployment. Monitoring, maintenance, incident response, and continuous improvement.
Building a Facility-Level Robot Data Model
Connecting organizations, facilities, workcells, robots, cameras, tasks, incidents, and service events into one operational graph.
Calculating the Economics of a Robotic Workcell
Hardware, integration, operation, and maintenance costs. How to model ROI for a physical-AI deployment.