The company emerged from research conducted during the founder’s PhD work at Imperial College London, where mathematical and epidemiological models were developed to forecast infection risk within hospital environments.
NEX’s platform applies artificial intelligence and predictive analytics to hospital data in order to forecast infection risks across wards, departments, and patient populations.
Key elements of the system include:
The technology combines mathematics, clinical evidence, epidemiology, and machine learning to model infection dynamics across healthcare systems.
According to the company, the predictive models have been validated using hundreds of thousands of patient records from hospital systems in the UK and Asia, demonstrating the ability to anticipate hospital‑onset infections days before they are clinically confirmed.
NEX reports that its system has been tested and evaluated across multiple healthcare environments internationally.
Evidence cited by the company indicates:
Public information about these deployments remains limited, and specific NHS trusts involved in the evaluations have not been publicly named in available reports.
In May 2026, NEX Health Intelligence raised €1 million in pre‑seed funding to advance its infection‑prediction technology.
The round was led by Brighteye Ventures and included participation from:
The new investment will primarily support further development and real‑world validation of the company’s AI platform.
Planned uses include:
The overall goal is to move the platform from research and pilot programs toward routine use in hospitals, helping infection‑control teams intervene before outbreaks spread.
If widely adopted, tools like NEX’s platform could mark a shift in how hospitals manage infectious disease risk. Instead of identifying outbreaks only after patients become infected, predictive systems aim to provide advance warning of transmission risks and enable preventive action.
While the technology is still in early deployment and validation phases, the approach reflects a broader trend in healthcare: using artificial intelligence to transform infection control from a reactive process into a predictive one.
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