Solvemed’s access to the $300m Isambard-AI supercomputer allows researchers to run medical AI experiments that were previously impossible due to computational limits.
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Solvemed Group has been granted access to Isambard-AI, a $300 million national investment that has made the United Kingdom home to one of the most powerful AI supercomputers on Earth. Systems at this level, ranked 11th globally on the TOP500 list and powered by over 5,400 NVIDIA Grace Hopper Superchips, are typically the domain of national laboratories, defense agencies, and large-scale climate science.
The scale is difficult to convey. If the entire global population performed calculations around the clock, it would take over two years to equal one second of Isambard-AI output. Certain categories of AI research in medicine have remained theoretical precisely because no accessible system could run them. That is no longer the case.
Access to infrastructure of this magnitude is rare. Only a handful of research institutions globally have the opportunity to work with systems at this level, and securing such a block of supercomputer time represents a significant allocation of national research resources.
Through the EyeWarn project, a £1.2 million collaboration with University of Essex researchers led by Dr. Javier Andreu-Perez, Solvemed will leverage this access to advance research into pupillary biomarkers and their physiological correlates.
One of the persistent challenges in clinical research is the tension between data quality and workflow disruption. Studies requiring research-grade physiological data have traditionally demanded dedicated protocols, specialized equipment, and additional clinical burden. Solvemed's PuRe Pupillometer eliminates this tradeoff. The device generates research-grade data through routine clinical use, integrating into standard examinations without requiring separate workflows or added steps. This means large-scale data collection can happen as a byproduct of everyday patient care rather than as a separate research activity.
When high-quality data collection becomes invisible within clinical practice, and when AI technologies can process that data at scale, research that once required years of dedicated effort becomes achievable within much shorter timeframes. The EyeWarn project represents an early example of what this combination makes possible.
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In today’s fast-paced clinical environment, swiftly and accurately evaluating a patient's neurological status is vital. Yet traditional pupillary assessments — based on visual observation — can be inconsistent and prone to subjective interpretation. To solve this long-standing challenge, Solvemed Inc. introduces a breakthrough in neurological evaluation: the Pupil Reactivity (PuRe) score.
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