NEX Health Intelligence, a healthcare AI company founded at Imperial College London in 2022, has raised €1m (approximately £865,000)  in pre-seed funding to advance a platform designed to predict how infections spread between patients and wards before transmission takes place. The round was led by Brighteye Ventures and brought total capital raised to around £1.21m.

Healthcare-associated infections represent one of the most persistent problems in hospital management. The World Health Organisation estimates that one in ten patients admitted to hospital acquired an infection during their stay. The consequences extend well beyond the individual patient: longer admissions, pressure on beds and clinical staff, avoidable deaths and costs that run into billions annually across global health systems. Existing approaches are largely reactive, identifying outbreaks after movement has already occurred.

NEX Health Intelligence is attempting to shift that calculus. Its platform analyses routinely collected hospital bed records to construct contact networks, mapping how patients and wards interact over time. From this data, the system identifies variables associated with infection transmission and generates predictions about where a pathogen is likely to move next, in some cases days before it does. Hospitals can act on these forecasts by isolating patients at risk, reallocating staff and making earlier clinical decisions. The underlying approach draws on advanced mathematical modelling developed during academic research at Imperial.

NEX was founded by Dr. Ashleigh Myall, whose interest in infection dynamics began while he volunteered in hospitals during the Covid-19 pandemic. Witnessing the rapid spread of infections among vulnerable patients in hospital wards inspired him to create computational systems for modeling this movement during his PhD in mathematics at Imperial College London. His research, supervised by Professor Mauricio Barahona, involved applying novel mathematical techniques to reveal transmission patterns that conventional surveillance methods cannot detect. This research formed the technical foundation for NEX.

Dr Myall said the problem he set out to solve was not the volume of hospital admissions but the speed at which infections travel once patients are inside. "I realised the real challenge wasn't just the number of admissions, it was how quickly infections spread between vulnerable patients already inside hospitals," he said. Imperial's entrepreneurial support infrastructure, including the Venture Catalyst Challenge, the MedTech SuperConnector programme and the Summer Accelerator, was credited by Dr Myall as providing the guidance needed to move from research into company-building.

The platform is currently operational across several hospital sites. In the UK, evaluation work is under way at two London NHS trusts, with a further deployment in north-west England. Internationally, the system has been installed at a major military hospital in Southeast Asia and is being expanded through a project at one of Malaysia's largest public hospitals. The current funding will be used to support further deployments in UK and international settings, complete regulatory and clinical safety processes required for the UK market, and generate clinical and economic evidence from live hospital environments.

Ben Wirz, founding partner at Brighteye Ventures, said the investment reflected the potential for AI to improve decision-making in high-pressure clinical settings. "AI has the potential to enable intelligent decision support in high-stakes environments, enabling healthcare teams to act faster and allocate resources smarter," he said.

The broader question for any predictive health tool is whether real-world performance matches the conditions under which it was developed. NEX has begun generating evidence from active deployments, which will be central to its regulatory pathway and to building confidence among NHS and international partners. How that evidence accumulates over the next phase of deployment will determine how quickly the platform can move from evaluation into standard clinical use.

‍