A closed loop of symptom tracking, diagnostics, AI insight, and clinician‑led action — designed for long‑term continuity. The aim is to reduce appointment bottlenecks and improve safety by standardising follow‑ups and screening.
User app
Lightweight daily/weekly check‑ins create a high‑signal timeline without burden. The app is deliberately calm: no “doom charts”, no alarmist labels — just clear, supportive reflection and next steps.
- Daily micro check‑in (30–60 seconds)
- Weekly review (sleep, mood, vasomotor, cognition, energy, pain)
- Context tags: stress, alcohol, exercise, cycle, meds, life events
- Education modules matched to stage and goals
Diagnostics
Diagnostics support baseline assessment, risk profiling, and safer HRT monitoring. The platform supports at‑home kits where clinically appropriate, plus local phlebotomy hubs for blood draws when needed.
- Baseline panels at onboarding
- Repeat testing schedule by subscription tier
- Status tracking: ordered → collected → results ready
- Plain‑English results explanation for patients
AI intelligence layer
AI analyses time‑series symptom patterns and merges them with biomarkers, treatments, and context. Output is explainable and designed for clinicians: trends, clusters, response signals, and risk flags — not black‑box predictions.
- Trend and anomaly detection (baseline vs change)
- Cluster detection (symptoms that rise together)
- Treatment response modelling (pre/post change)
- Risk prompts (bone, cardio‑metabolic, thyroid, mental health)
Clinician portal
Clinicians work from a daily cockpit that prioritises patients and tasks. A longitudinal timeline reduces recall bias and supports safer iteration of treatment, with documentation and audit trails built in.
- Task list: new consults, follow‑ups, labs to sign‑off
- Patient timeline: symptoms + labs + treatments overlay
- Decision support: suggested next steps for clinician review
- Documentation: SOAP drafts, letters, structured notes
- Patient completes intake questionnaire
- Appointment happens weeks later
- Symptoms summarised from memory
- Clinician adjusts treatment based on limited context
- Follow‑up scheduled (often delayed)
- Patient completes micro check‑ins continuously
- Timeline shows baseline and meaningful change
- AI highlights response to recent dose change
- Clinician reviews and confirms next step
- Care plan updates immediately + proactive testing reminders