The independent supervision layer for Physical AI
Machines now make decisions in the physical world. Terbine AI is building STRATA to watch them independently of the vendors that build them, and to step in before a failure or misuse becomes an incident.
Physical AI is scaling faster than anyone can supervise it
Battery storage sites, delivery robots, drones and robotaxis are going live in large numbers. Each runs on its maker’s software and reports to its maker’s dashboard. Nobody independent is watching across them.
When something goes wrong, it falls into a gap. Cybersecurity teams protect networks. Physical security teams protect buildings. Neither owns a machine that is hacked, misused or simply failing. That’s where Terbine AI comes in.
What we do
Battery storage supervision (in development)
STRATA (System for Tracking, Routing, and Autonomous Task Administration) is being designed to watch battery storage systems from any vendor, predict thermal runaway and act before a fire starts. For AI data centers, utilities, defense installations and their insurers.
Autonomous fleet supervision (in development)
Being designed to give public-safety agencies and military installations an independent view of robotaxis, delivery robots and drones, flagging machines that are failing, hijacked or used as weapons.
Physical AI advisory (available now)
Threat assessments, tabletop exercises and response plans for the risks of Physical AI, delivered by Terbine AI directly.
Where we are
STRATA’s foundations, the Policy Engine for governed data sharing and the Mission Control console for Human-ON-the-Loop supervision, have been developed and demonstrated on synthesized data and are assessed at technology readiness level 5. The next step is field validation with sandbox partners: operators and agencies who help shape the first applications and get early access. Physical AI advisory is available today.
Both applications are dual-use: they apply to civilian operators and public-safety agencies, and to defense installations and the autonomous systems operating on them.
Vendors shouldn’t be the only ones grading their own machines
Vendor-neutral
One view across every manufacturer, so a mixed site or fleet is supervised as a whole.
Predictive
Designed to spot the patterns that come before a failure, not just the alarm when it starts.
Able to act
Designed around Human-ON-the-Loop control in Mission Control: the AI acts in split seconds, a person sees it at the same moment, and every action is logged.
Delivered and fully paid contracts for the U.S. Air Force (AFWERX) and the U.S. Department of Energy · Formal teaming agreement with the UNLV College of Engineering · NVIDIA Inception member · Alchemist Accelerator portfolio company · Publisher of The Physical AI Report
Who owns your Physical AI risk?
If the answer is “no one, exactly,” let’s talk.