Live update: AI Pathfinder: Delivering Sovereign AI Infrastructure for resilient UK growth
Welcome to AI Pathfinder
AI Pathfinder delivers next-generation, sovereign-owned AI to empower leaders in healthcare, finance, defence, logistics, FMCG, and beyond.
At AI Pathfinder, we think "keeping the data local" is table stakes, but by no means sufficient to be classified Sovereign AI. We believe Sovereign AI must actually benefit a nation, not simply profit from it. Our definition of Sovereign AI has four pillars:
Purpose Built
AI Pathfinder controls every layer of the AI stack. This vertical integration removes third-party risk, guarantees full sovereignty, and ensures that sensitive workloads remain entirely within sovereign jurisdiction.
AI Pathfinder’s first sovereign AI campus, delivering 406mw of secure, high-performance compute directly alongside renewable generation. Chelveston showcases the speed and efficiency of Pathfinder’s vertically integrated model - combining land, power and data centre infrastructure in one location to provide a resilient, low-latency foundation for launching large-scale AI workloads.
Ayrshire’s i3 Campus is Pathfinder’s 1–1.5GW flagship site, designed as a national-scale AI factory for defence, health and critical industries. Integrated with renewable energy and engineered for hyperscale expansion, the campus anchors the northern segment of the sovereign AI mesh - delivering massive compute capacity, secure operations and strategic resilience for the UK’s most sensitive workloads.
The Gravity Campus in Somerset is an 830MW green AI super-campus located within one of the UK’s most energy-resilient innovation clusters. Purpose-built for sustainable, hyperscale compute, it enables advanced AI research, automation and industrial applications while operating on a sovereign foundation of land, power and vertically engineered data centre infrastructure.
Leveraging machine learning, NLP, and computer vision to automate and optimise complex, cognitive processes. AI systems that learn from data (structured & unstructured) and make decisions to streamline end-to-end workflows, significantly boosting efficiency and accuracy.
AI-powered software agent designed to help users perform a wide variety of tasks or services based on voice or text commands. Examples include Coding Assistants, Customer Service Assistant, Intelligent Search Assistant, and multi agent systems.
Dynamic virtual replica of a physical object, process, or system—such as a jet engine, a manufacturing floor, or an entire city. It uses real-time data collected from Internet of Things (IoT) sensors on the physical counterpart to accurately reflect its current state, performance, and behaviour. This continuous data flow creates a living model that enables users to run simulations, test "what-if" scenarios, predict failures (like predictive maintenance), and optimise performance without affecting the real-world asset.
Integration of Artificial Intelligence algorithms (like machine learning and computer vision) with physical, embodied systems like robots, autonomous vehicles, and drones. Allows machines to move beyond pre-programmed routines, enabling them to learn, adapt, and interact safely with unpredictable physical environments, which is essential for applications in manufacturing, logistics, and healthcare.
Delivering massive parallel processing capability required for computationally intensive tasks like training large language models, deep learning, and complex scientific simulations, without the need for significant capital investment in hardware.
Fully managed platform for deploying, scaling, and managing containerized AI workloads across AI infrastructure. This service handles the complexity of setting up and maintaining the Kubernetes control plane, worker nodes, and underlying networking, allowing developers to focus solely on deploying their containers and optimizing their AI applications.
Integrated environment that provides all the tools and infrastructure needed to build, deploy, and manage machine learning models, from data preparation to model serving. This fully managed service abstracts away complex operational tasks, allowing data scientists and developers to rapidly iterate on experiments and scale their models into production efficiently.
Securely store, prepare, process, and enrich data specifically for training and operating Artificial Intelligence and Machine Learning models. These services include essential functions like data annotation and labelling, quality assurance, and ethical sourcing, ensuring models are trained on high-quality, accurate, and unbiased data. Certified to Sovereign Data Protection standards.