— PHYSICORE DEPLOYMENT INDEX
PHYSICAL AI IN THE REAL WORLD.
A structured view of Physical AI systems across real-world sectors, workflows and deployment stages, with evidence clearly separated by source and verification level.
The Index is designed to help operators understand what is being deployed, where it is being used and how strong the underlying deployment evidence is.
— Sector coverage
TRACKED ACROSS REAL OPERATING SECTORS.
— The Index
DEPLOYED SYSTEMS.
117 of 117 records
— METHODOLOGY
DEPLOYMENT CLAIMS ARE NOT THE SAME AS DEPLOYMENT EVIDENCE.
A robot operating in a customer environment tells us that deployment has occurred. It does not, by itself, establish task performance, reliability, robustness, economics or generalisation. Physicore separates these questions and increases evidence confidence as deployments move from public reporting to buyer verification, direct observation, repeatable testing and multi-site validation.
Current system identified and mapped from public information.
Published evidence from the builder, customer, partner or research source.
Deployment information confirmed by the operator using the system.
Physicore directly observes the system operating under a defined measurement protocol.
Physicore runs repeatable testing against defined real-world tasks and conditions.
Comparable Physicore evidence across multiple real operating environments.
— WHAT PHYSICORE MEASURES
CAPABILITY
Can the system complete the required task?
RELIABILITY
Can it keep doing so without excessive failure or human intervention?
ROBUSTNESS
Does performance hold when real-world conditions change?
RECOVERY
What happens when the system fails?
ECONOMICS
Does the deployment create sufficient operational value?
GENERALISATION
Does performance transfer across tasks, sites and conditions?
PHYSICAL AI IS VERSIONED
Robot hardware, models, policies and software can change materially between deployments. Physicore therefore treats performance evidence as specific to the system configuration, software or model version, task, environment and date on which it was observed.
DATA FRESHNESS
Physical AI changes quickly. Physicore periodically reviews system status, deployment information and source availability. Each profile records the date it was last verified.
— TECHNOLOGY LANDSCAPE
THE INTELLIGENCE LAYER.
Foundation models and enabling Physical AI platforms shape what robots can learn and how capability transfers across embodiments. They are tracked separately because they are not directly comparable with deployed robotic systems.
FOR DEPLOYERS
Move from claims to evidence.
Use the Index to understand the market, identify systems relevant to a workflow and determine what evidence should be required before pilot approval, deployment or multi-site rollout.
FOR BUILDERS
Prove performance in reality.
Physicore's evidence framework provides a structured route from public deployment claims to buyer-verified, observed, tested and multi-site evidence.