ZestyCoach is developed using established, peer-reviewed research in exercise physiology, women's health, and behavioral science. We're actively preparing for formal research studies and validation as the platform evolves.
Exercise physiology, women's health, and behavioral science foundations
Academic collaboration in progress with University of Tennessee
Founder-led, designed for ethical research from day one
ZestyCoach is built using established research in women's health and physiology. We're preparing to launch our own research cohort to validate and refine our approach with real-world data.
Comprehensive analysis of peer-reviewed research in exercise physiology, women's health, and menstrual cycle impacts on performance.
Collaboration with Dr. Kelley Strohacker (Exercise Physiology) and Dr. Hector Santos-Villalobos (Machine Learning) to ensure scientific rigor.
Working with University of Tennessee to prepare for formal research studies and validation as the platform evolves.
Building ethical data collection practices from day one, designed to support future research while protecting user privacy.
Published research shows Heart Rate Variability fluctuates across menstrual cycle phases—we're using this foundation to build adaptive training models.
Emerging research suggests training adaptation to cycle phases may improve outcomes—we're building tools to test and validate this approach.
Combining cycle data, daily readiness, and user input to create holistic coaching—a model we'll validate with our upcoming research cohort.
Every woman's body responds differently—our AI is designed to learn and adapt to individual patterns over time.
We're building the foundation for rigorous validation and future publications
Status: In Progress
Launching voice-first AI coaching with privacy-first data collection to understand how women respond to cycle-aware, readiness-driven training guidance.
Status: In Planning
Preparing research cohort to formally study the impact of cycle-aware, biometric-driven coaching on women's training outcomes, consistency, and wellbeing.
Target: 2027+
Our goal is to publish validated findings on cycle-aware AI coaching effectiveness, contributing to the growing body of research on women's health optimization.
Experienced advisors helping us build with scientific rigor
Exercise Physiology Advisor
University of Tennessee
Dr. Strohacker provides guidance on exercise science foundations, women's health research, and academic collaboration as we prepare for formal research studies.
Machine Learning Advisor
AI & Data Science
Dr. Santos-Villalobos advises on machine learning architecture, data modeling, and ethical AI practices to ensure our technology is built on sound principles.
We believe women's health deserves the same scientific rigor as elite sport — and we're building the foundation to do it right.
Join our early access program and help shape a new approach to women's health optimization.