Research
Advancing personal pattern recognition
Cognitive State Recognition
Our research focuses on identifying and predicting cognitive states through pattern analysis of personal data spanning years, not moments.
Temporal Pattern Analysis
10-Year Data Windows
Traditional AI analyzes moments. Sovria analyzes decades. By processing patterns across 10+ years of personal data, we identify cognitive rhythms invisible in shorter timeframes.
- Multi-year pattern detection
- Seasonal cognitive variations
- Long-term performance trends
State-Aware Response
Cognitive Load Adaptation
Sovria adapts its responses based on your current cognitive state, not just the clock. Complex analysis during peak focus, simple tasks during recovery.
- Real-time state detection
- Response complexity matching
- Cognitive load optimization
Pattern Emergence
Invisible Correlations
Discover patterns between seemingly unrelated data points. Exercise timing affects decision quality. Meeting length impacts creative output. Sleep patterns predict focus windows.
- Cross-domain correlation
- Non-obvious relationships
- Predictive pattern modeling
Key Findings
Improvement in decision quality when aligned with cognitive peaks
More patterns detected in 10-year data vs 1-year analysis
Accuracy in predicting optimal work windows
Publications
Research papers and technical documentation coming soon for founding members.
Join Our Research
Founding members shape our research direction through their patterns and feedback.
Apply for Founding Membership