How NEX Health Intelligence Uses AI to Predict and Prevent Hospital Infections

Healthcare‑associated infections remain one of the most persistent and dangerous problems inside hospitals. A London health‑tech startup, NEX Health Intelligence, is attempting to tackle the issue with artificial intelligence that predicts where infections will appear and spread before outbreaks occur.

Founded at Imperial College London, the company is developing an AI‑driven infection intelligence platform designed to help hospitals detect risks earlier and prevent dangerous outbreaks, particularly those involving antimicrobial‑resistant pathogens.

Why NEX Health Intelligence Was Created

Hospitals worldwide struggle with healthcare‑associated infections (HAIs)—infections patients acquire during medical care. These infections can spread quickly within hospital environments, especially when caused by drug‑resistant bacteria often referred to as “superbugs.”

Traditional infection control systems typically identify outbreaks after cases begin appearing, limiting the ability of hospitals to intervene early. NEX was created to address this gap by providing predictive tools that allow infection‑control teams to anticipate outbreaks instead of reacting to them.

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.

How NEX Uses AI to Predict Hospital Infections

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:

• Predictive infection modeling: AI models estimate where infections or antimicrobial‑resistant organisms are likely to appear next in a hospital.
• Transmission‑risk analysis: The platform analyzes patient data and hospital workflows to identify potential transmission pathways.
• Early‑warning insights: Infection‑control teams receive forecasts that allow earlier intervention, such as isolating patients or changing clinical protocols.

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.

Where the Platform Is Being Tested and Deployed

NEX reports that its system has been tested and evaluated across multiple healthcare environments internationally.

Evidence cited by the company indicates:

• Validation studies using patient records from major hospital systems in the UK and Asia.
• Evaluation projects with NHS organisations, including trials across two London NHS Trusts.
• Deployment of the surveillance platform in Thailand’s largest military hospital, a large healthcare facility with high infection prevalence.

Public information about these deployments remains limited, and specific NHS trusts involved in the evaluations have not been publicly named in available reports.

The €1 Million Funding Round

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:

• Adeline Arts & Science
• AFI Ventures
• Momentous Ventures
• Conception X Angel Syndicate
• Additional industry angel investors

The company reports total funding of about £1.2 million to date following this round.

How the Funding Will Support Expansion

The new investment will primarily support further development and real‑world validation of the company’s AI platform.

Planned uses include:

• Enhancing predictive models that forecast infection outbreaks in hospitals
• Expanding clinical evaluations with healthcare partners
• Progressing toward UK regulatory approvals for broader deployment
• Scaling the technology for wider use across healthcare systems

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.

A Shift Toward Predictive Infection Control

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.