Pause-Health.AI · Premium FemTech Intelligence

Elevating menopause care with precision, empathy, and clinical AI

Waking at 3 a.m. drenched in sweat. Losing words mid-sentence. Feeling anxious for no reason you can name. Aching joints, a racing heart, a body that suddenly feels unfamiliar. If that sounds like you — you're not imagining it, and you're not alone. Two-thirds of women are initially misdiagnosed, and the average wait for an accurate answer is 2.5 years. Pause helps bring your whole story together — sleep, mood, cycles, hot flashes — and points your care team toward the right next step sooner, with every step explainable.

For care teams, that becomes a refined decision layer for perimenopause and menopause: multimodal signal intake, clinically explainable triage, and personalized next-step pathways designed for women in midlife. Built provider-first on Salesforce Health Cloud, MuleSoft, and the JupyterHealth FHIR substrate.

Read the investor brief →Touch the prototype →Read the code →

Built by Maggie C. Hu · LinkedIn · Founder. Reach out at /contact.

Today's reality

Numbers that survive a curl

Provider-graph Phase 2 shipped. Five counts below ride on the response of every /api/mulesoft/providers call under provenance.dataset — a reader can verify them in one shell command. Insurance acceptance is synthetically derived per-NPI today (the chips are a soft filter, not a guarantee); MSCP coverage waits on a Menopause Society partnership. Closed-loop outcomes scoring activates with referral volume.

Read the provider-graph brief →Browse the directory →Curl the contract →

What's live today

Touch the working surfaces, not just the deck

Four end-to-end capabilities you can run against the prototype right now. Each card opens the matching /demo page where the persona, the API surface, and the trace spans are inspectable.

Built in the open — 175 commits since May 24, 2026.

See what shipped →See what's coming →

For investors + partners

Read the thesis

Two arcs: the investment thesis (strategy, market, customers, competition) and the architecture story (Agentforce, MuleSoft, MCP, Data 360, JupyterHealth, DBDP, Agent Fabric). Per-card proto-vs-prod tables and verifiable live API CTAs.

Open the brief →Full proposal →

For builders + clinicians

Touch the prototype

Six demo personas, one persona-preserving journey: intake → Care Detail → Care Router → Agent Fabric trace inspector → outcome analytics. Real Salesforce Health Cloud grounding when configured; deterministic mock otherwise.

Start the journey →Trace inspector →