A British physical-AI product company
Turning business intent and operational knowledge into safe, dependable work for intelligent robots.
Our vision
Project Stone connects business knowledge, operating intent and the physical world so robots perform useful work safely and dependably.
The company has substantial support from multiple investors. Its founders bring extensive experience across technology, electronics, semiconductors, software, company building, investment and finance.
Why now
Robotic hardware is becoming more capable and substantially less expensive. At the same time, advances in AI, perception, simulation and robot learning are expanding what these machines can do.
Yet there remains a large gap between possessing a capable robot and operating a dependable business application. Businesses already hold much of the required knowledge—in plans, product records, layouts, workflows, policies and operating systems—but robots cannot readily interpret it or turn it into qualified physical work.
The platform could support applications in areas such as retail, logistics, facilities management and other human-centred commercial environments.
The product
Three connected layers establish what the business needs, turn that intent into qualified work, and supervise execution continuously in the real world.
Builds a business and physical-world ontology from existing operational knowledge: what exists, where it belongs, what “correct” looks like and which outcome is intended.
Translates business intent into governed robotic workflows. It identifies the gap between expected and actual conditions, plans the work and qualifies it against available capabilities and constraints.
The always-on common-sense and safety layer. It monitors people, objects and changing conditions, verifies results, and decides when to continue, stop, recover, replan or escalate.
People
CTO designate · anonymised profile
The CTO designate brings more than 15 years of experience across robotics research and industrial development, including senior research roles and leadership of multidisciplinary teams delivering end-to-end autonomous robotic systems.
His expertise spans task and motion planning, perception, manipulation under uncertainty, autonomous navigation, system integration, failure interpretation and recovery. He has also worked with modern robot-learning methods, including vision-language and vision-language-action systems and foundation-model-based autonomy.
He holds a PhD in robotics, has received doctoral distinction and has authored more than 30 peer-reviewed publications. Identifying details are withheld at this stage.
Our immediate purpose is to build the first operational version of the platform around a tightly defined commercial use case, demonstrate measurable value in a real environment and establish the evidence for further funding. Our longer-term objective is a reusable platform that extends across applications, machines and international markets.
Project Stone · Priory House