Khalisa by Evia Wellness — Cycle-Aware Hormone Intelligence Platform
Built the first AI platform that treats the female hormone cycle as a vital sign — a patent-pending hormonal digital twin that unifies wearables, symptoms, labs, and medical records into one clinician-supervised system. Not a period tracker. A clinical intelligence platform.
Women's healthcare has a measurement problem. Heart rate, blood pressure, and glucose are all treated as vital signs — tracked continuously, interpreted clinically, acted on early. The female hormone cycle, which governs sleep, mood, metabolism, cardiovascular risk, and bone density across four decades of life, is treated as lifestyle data.
The consequence shows up most sharply in perimenopause, where 96% of women who need hormone therapy never receive it. Not because the therapy doesn't exist, but because nobody is measuring the signal that would indicate it. Evia Wellness set out to change that with Khalisa™ — a platform that models each woman's hormonal biology continuously, predicts where she is heading rather than reacting to where she has been, and puts a clinician in the loop on every decision. Bitsol built it.
Turning a cycle into a clinical signal
Hormone health generates enormous amounts of data across wearables, symptom logs, lab panels, and medical records — none of it structured, connected, or clinically actionable. Khalisa™ needed to unify all four into a system a clinician could safely prescribe from.
- The hormone cycle drives sleep, mood, metabolism, cardiovascular and bone health, yet sits outside standard clinical monitoring
- Care is reactive: women present with symptoms long after the underlying shift began
- Perimenopause is the sharpest failure point — 96% of women who need hormone therapy never receive it
- Existing consumer apps predict periods, not disease pathways
- Continuous wearable streams — sleep, heart rate variability, body temperature — arriving in three different vendor formats
- Daily subjective symptom logs with no structure a model can learn from
- Quarterly lab panels in inconsistent units and reference ranges
- Medical records that clinicians trust but algorithms can't parse
- All of it PHI, all of it requiring HIPAA-grade handling from the first line of code
A hormonal digital twin, with a clinician in the loop
Computational modeling of each woman's reproductive lifespan, fed by a unified data layer, surfaced through a clinician portal with review and override at every step.
- Patent-pending AI architecture using computational modeling
- Maps each woman's position across her reproductive lifespan
- Predicts which disease pathways are emerging, rather than reporting what already happened
- Enables cycle-aware medication titration so therapy adapts to her biology
- Daily cycle-aware predictions surfaced through a calendar-based interface
- Wearable integration across Apple Health, Oura, and Fitbit
- Symptom and cycle tracking with pattern recognition
- Lab upload with structured normalization to consistent units and ranges
- Medical record ingestion into the same patient model
- Clinician portal with full review and override workflows
- Clinician-approved therapy schedules surfaced to the patient
- No autonomous clinical decision — a licensed clinician signs off
- HIPAA-compliant architecture, BAA-ready, PHI encrypted at rest and in transit
- Built with guidance from experts in computational pharmacology, clinical pharmacy, and women's health
Khalisa™ launches into perimenopause and extends across the full female lifespan — puberty, postpartum, and menopause.
What changed — measurably
Khalisa™ moves women's healthcare from reactive to preventive. Rather than waiting for a woman to present with symptoms, the platform models her hormonal trajectory continuously and flags emerging pathways while there is still time to intervene.
The hormone cycle treated as a continuously monitored vital sign, not lifestyle data
Four previously siloed data sources unified into a single patient model
Predictive rather than retrospective — emerging disease pathways surfaced early
Cycle-aware titration lets therapy adapt to biology instead of a fixed schedule
Every clinical recommendation reviewed and approved by a licensed clinician
Architecture designed to extend from perimenopause across the full female lifespan
Straight From The Client
Bitsol helped the client launch the beta, and the end client used the platform. The end client received daily AI symptom forecasts from cycle, wearable, and lab data, replacing guesswork with guided care. The team delivered the prototype and MVP on time and was very responsive.
Related Work
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