The Mentis Care Platform:
From Continuous Monitoring to Predictive Neurological Care
The Mentis Care Platform is designed to be an end-to-end neurological intelligence system designed to connect patients, caregivers, clinicians, and partners on a shared AI-powered, longitudinal foundation. Every interaction will contribute to a structured longitudinal record that supports better visibility today and more advanced intelligence for the future.
Reframing epilepsy Monitoring
From Isolated Observations to Longitudinal Insight
In-clinic epilepsy monitoring offers limited visibility into a condition that evolves over days and nights and across real-world contexts.
Epilepsy care increasingly demands objective insights that go beyond isolated recordings. Monitoring neurological activity during everyday life helps clinicians understand both individual events and how they accumulate over time.
The clinical goal remains the same. The method of generating insight needs an upgrade.
Continuous, at-home EEG monitoring enables several distinct capabilities:
Seizure Detection
Recording events in real time provides objective, time-stamped seizure records without relying solely on retrospective self-reports.
Seizure Prediction
Identifying and alerting to imminent risk empowers patients and caregivers to prepare and respond before a seizure occurs. As seizure data accumulate over time, objective records can be analyzed to reveal patterns, cycles, triggers, and treatment response.
Our Platform
One Platform. Every Stakeholder. One Source of Truth.
Mentis Care is building an integrated platform focused on wearable EEG and AI-driven signal analysis, designed to work outside controlled clinical settings.
The platform allows extended EEG collection in daily life, combined with algorithms that analyze signals continuously in real time. Secure data infrastructure enables aggregation and review over weeks and months through interfaces for clinicians and patients.
Foundation Model: Contextualized Learning
Seizure activity is infrequent, heterogeneous, and highly variable across patients, contexts, and time. AI models trained on short EEG segments often struggle to generalize beyond narrow conditions or controlled datasets.
Mentis Care is using a foundation model approach that learns the underlying neurological structure from a large longitudinal EEG dataset before being adapted for seizure detection and prediction.
By learning shared representations across individuals and contexts, this approach aims to support more reliable signal interpretation as data scale, while remaining adaptable to various clinically relevant goals.
Built To Scale
The Mentis Care Platform is designed to grow in value with every patient enrolled and every month of data generated.
Data Basis: initial platform generates continuous longitudinal data: seizure events, EEG signals, medication adherence, triggers, and wearable data. This dataset is the irreplaceable foundation for everything that follows.
AI Models: Detection first, then individualized prediction. AI foundation models trained on longitudinal data enable real-time seizure detection, and as patient-level data matures, individualized prediction becomes possible for certain conditions.
Integrated Intelligence: The mature longitudinal dataset will enable risk stratification, multi-disease outcome forecasting, and precision medicine drug response tools. This is where platform value compounds exponentially — for patients, clinicians, and pharma partners alike.
Impact
Supporting Clinical Decisions Beyond the Clinic
For patients:
Continuous monitoring increases visibility into their condition and provides early warning of impending seizures.
For families:
Sustained monitoring offers peace of mind through ongoing observation and timely alerts.
For clinicians:
Objective seizure records collected over time support clearer assessment of seizure burden, treatment response, and medication titration.