Advanced tools for real-time behavioral data collection, sequential analysis, and AI-powered insights.
Observerware delivers precise, real-time tools for observing, coding, and analyzing complex human and non-human behavior. It combines proven sequential analysis methods with modern AI to turn raw observational data into actionable, measurable insights.
Designed for researchers, clinicians, educators, and performance professionals who need rigorous, technology-enhanced behavioral measurement.
Originally developed as BEST (Behavioral Evaluation Strategy and Taxonomy) and later ObserverWare by Thomas L. Sharpe and John Koperwas.
Co-authored the definitive guide Behavior and Sequential Analyses: Principles and Practice (SAGE Publications), establishing rigorous methods for multi-event, time-based behavioral observation.
Real-time data collection and sequential analysis platform used in research, teacher training, clinical settings, and ABA practice. Later evolved into ObserverWare with continued development through 2012+.
Bringing the original vision into the age of intelligent systems.
Hybrid AI systems that combine symbolic reasoning with neural pattern recognition for interpretable, high-accuracy behavioral coding and sequential modeling.
Live multi-event observation with AI-assisted tagging, anomaly detection, and automated reliability scoring — deployable on edge devices or in the cloud.
From raw observational streams to predictive models, intervention recommendations, and longitudinal behavioral analytics — all grounded in validated methodology.
Observerware is being rebuilt from the ground up with modern AI, local-first architecture, and the same commitment to rigorous behavioral science that defined the original work.