Evia Wellness
Evia Wellness develops Khalisa, a predictive platform that treats the female hormone cycle as a vital sign for personalized medicine. The platform offers decision support for clinicians treating perimenopause, a mobile app for women with daily cycle-aware predictions, and longitudinal data analytics for researchers studying women's health.
- Artificial Intelligence
- Data & Analytics
- Digital Health
- Healthcare Technology
- Software Only
- Wellness & Fitness Technology
Funding
Founders
Product
Problem
Women's hormonal health has been historically tracked using tools designed around male biology and static single-point measurements, failing to account for the dynamic, non-stationary nature of the female endocrine system. This results in misdiagnosis, delayed treatment, and generalized protocols that overlook individual biological variability across the full female lifespan.
Solution
Evia Wellness offers the Khalisa platform, the first predictive system that uses the hormone cycle as a vital sign to support personalized care. For clinicians, it provides decision support for diagnosing and treating women in perimenopause. For women, a companion mobile app delivers daily, predictive, personalized menstrual support to reduce the cognitive burden of tracking symptoms. For researchers, Khalisa collects and analyzes multi-modal longitudinal data on women aged 18 and older to generate insights and identify treatment options. The platform integrates lab results and wearable device data to enable continuous monitoring and cycle-aware predictions.
Target Audience
Primary users are clinicians treating perimenopausal women, women aged 18 and older seeking personalized menstrual and hormonal health support, and researchers studying women's health across the lifespan.
Features
- Patent-pending predictive algorithms that model non-stationary hormonal variability across the full female lifespan
- Clinician decision-support dashboard for perimenopause diagnosis, assessment, and treatment recommendations
- Mobile app with daily cycle-aware predictions, personalized symptom tracking, and health trend visualization
- Secure integration with wearable platforms including Apple Health, Oura, and Fitbit for continuous health metric import
- Multi-modal longitudinal data collection and analytics engine for research on women aged 18 and older
- HIPAA-aligned security infrastructure with TLS in-transit and AES-256 at-rest encryption