Intelligence Systems
CYNAERA’s Intelligence Systems are designed to surface what traditional tools overlook, forecasting disruption across health, infrastructure, finance, education, and climate. Each system integrates real-time signals, structural data, and adaptive modeling to support smarter decisions in high-stakes environments.
Whether it’s mortality risk, institutional lag, digital unrest, or environmental volatility, CYNAERA Intelligence Systems deliver foresight where it matters most.
Empowering Your Systems
Real-Time Population Mapping
S³ Model™ pulls from public social media signals to estimate true activity, interest, and need from health to migration to education.
Signal-Based Risk Detection
RAEMI™, and PULSE™ modules expose where disruptions are forming, whether in water systems, disease trends, school absences, or infrastructure failure.
Environmental Risk Forecasting
VitalGuard™ can map mold risk, air toxicity, wildfire exposure, and climate pressure, including for zones where traditional monitoring fails.
System Monitoring for Large Institutions
EASE™, RePath™, and BRAG™ modules flag failure patterns in hospital systems, insurance, education, law enforcement, and supply chains.
Top 12 Core Modules
CCUC
Reconstructs the true scale of chronic illness in U.S. data, adjusting for systemic underreporting and medical gaslighting. US-CCUC has already shown that Long COVID affects 35M–50M Americans, far more than federal estimates.
ICDx
Detects misclassified or undiagnosed chronic illness using pattern analysis and delay mapping. ICDx flags underrecognized conditions like PANS, Chronic Lyme, and POTS in large datasets, helping agencies and AI tools improve diagnostic accuracy.
RAEMI
Measures excess mortality and habitual loss across regions, populations, and conditions, correcting traditional statistics. It identifies deaths linked to structural failures, delayed care, environmental risk, and diagnostic neglect. It is a powerful tool for forecasting hidden impact in sectors like maternal health.
S³ Model
Turns public online information into prevalence and trend scores. S³ Model bridges the gap between lagging institutional data and real-world health realities, making it critical for early warning, flare forecasting, and narrative observations.
VitalGuard
Uses real-time environmental data, air quality, wildfire smoke, humidity, and mold risk to predict symptom flare-ups in patients with chronic illness. VitalGuard is ready to be applied to FEMA planning, climate-health alerts, and surge forecasting for ERs.
EASE
Grades hospitals and health systems on how well they serve patients with complex chronic conditions. EASE incorporates user experience, discharge safety, telehealth quality, and demographic gaps to create an institutional scorecard.
PULSE
Analyzes what stories are rising and what’s being ignored in public discourse. PULSE tracks underreported conditions, misinformation, narrative suppression, and emergent health threats using a blend of urgency, visibility, and testimonial weight.
RAVYNS
Detects hidden patterns of abuse, medical neglect, and systemic harm by correcting for underreporting, digital silence, and demographic suppression. It blends signal observation with mortality overlays, delivering composite estimates of harm in populations often missed by official stats.
NeuroVerse Core
Clusters cognitive, behavioral, and neurological symptoms tied to infection-associated conditions. NeuroVerse Core supports both diagnosis and research by revealing the hidden burden of post-viral brain dysfunction, especially in ME/CFS, and youth neurodivergence.
CLARITY
Quantifies how climate change intensifies chronic illness risk. CLARITY simulates environmental triggers, like temperature spikes or air quality drops and shows how these stressors interact with condition sensitivity and more. The score predicts flare intensity, infrastructure strain, and needed interventions.
Adversa
The system tracks rare post-vaccine and immune-triggered symptom clusters across populations and regions, detecting emerging safety signals early. Built for adaptability, it enhances surveillance in real-world, a variety of settings where traditional reporting often falls short.
TriMod
Maps symptom interaction and risk burden in patients with three or more co-occurring chronic conditions. TriMod has unique parameters that are great for use in hospitals, advocacy groups, rare disease organizations and more to get a more accurate estimate of illness burden in populations.
The CYNAERA Intelligence Footprint
50
Core Engines
5B+
Unique AI Modules
1M+
Simulation Profiles
180+
Countries Analyzed
32
Sectors Activated