Rigorous Science.Reliable Predictions.
Our technology is built on rigorous science, validated against real-world outcomes, and continuously refined through machine learning trained on over 10 million environmental data points.
Four Disciplines.
One Prediction Engine.
NEIMUS360's predictive accuracy is built on the intersection of genomics, artificial intelligence, pattern recognition, and rigorous field validation.
DNA & Data Points
Mold DNA sequencing identifies problem species and genetic biomarkers, distinguishing harmless spore presence from genuine colonisation risk.
Machine Learning
Trained on 10 million+ data points from the Caribbean - one of the world's most demanding environments for mold prevention. Every building monitored makes the model smarter.
Pattern Recognition
AI detects the precise convergence of humidity, temperature, and organic material that precedes mold growth - predicting risk before it becomes visible.
Validated Predictions
Every prediction is validated against real-world outcomes. Field-tested at the Barbados National Archives, so every alert NEIMUS360 issues is grounded in empirical evidence.
Mold Growth Index 2.0
Our proprietary MGI 2.0 algorithm continuously analyses environmental conditions to identify mold formation risk days before it becomes visible or damaging.
NEIMUS360 detects risk. Full intervention window available.
Conditions are building. Remediation should be mobilised.
Intervention window closing. Immediate action required.
Traditional systems alert here. Damage is already occurring.
Traditional systems detect mold only when visible. NEIMUS360 predicts growth 24-72 hours in advance.
The Science Behind
Every Prediction We Make
Every NEIMUS360 prediction is underpinned by three core disciplines - environmental science, machine learning, and validated field research - each rigorously applied to ensure accuracy, reliability, and defensible outcomes.
Conditions That Precede Growth
Mold growth requires a precise convergence of conditions: sustained relative humidity above 60%, temperatures between 15-30°C, and the presence of organic substrate material. Our sensors track all relevant environmental variables simultaneously and continuously - detecting the specific multi-variable combination that creates favorable growth conditions days before spore colonisation begins.
Intelligence That Learns From Every Building
Our AI has been trained on 10 million+ data points collected across Caribbean conditions - one of the world's most challenging environments for mold prevention, given the combination of sustained heat, humidity, and tropical weather patterns. The model learns continuously from every deployment, improving prediction accuracy with each building monitored and each environmental event recorded. Every facility makes the platform smarter for all others.
Accuracy Confirmed Against Real-World Outcomes
Every NEIMUS360 prediction is compared against real-world outcomes in a continuous validation loop. At the Barbados National Archives - a facility housing irreplaceable historical documents and subject to critical humidity control requirements - our system achieved consistent accuracy in predicting environmental risk before document damage occurred. This field validation underpins the reliability of every alert our platform issues, ensuring that when NEIMUS360 signals a risk, it is actionable and grounded in empirical evidence.
Grounded in Science.Built for Certainty.
NEIMUS360 is not a monitoring system - it is a predictive intelligence platform grounded in rigorous science. Request a technical brief to review the data behind the platform.