Customer selection
Health system + value-based payer ICPs, buying committee personas, market sizing, and sequencing.
Investor brief · Pause-Health.ai
Premium menopause intelligence for modern provider organizations
Pause-Health.ai transforms fragmented menopause care into an elegant, measurable, and clinically explainable workflow built for provider excellence — EHR-native, never a sidecar.
- Focus cohort: women ages 40-60 navigating perimenopause and menopause with nuanced, evolving symptom profiles.
- Research~67% are initially misdiagnosed; the average path to accurate diagnosis can extend to ~2.5 years.
- Target89% AI-assisted triage accuracy with transparent, evidence-linked rationale.
- FHIR-native data + wearable biomarkers create a real-time menopause intelligence layer.
- PlanProvider-first B2B model delivering measurable ROI and durable ARR growth.
Arc A · Investment thesis
The strategy + market briefs (six)
Why Pause-Health.ai, why now, who buys, what the competitive landscape looks like, and how we will evaluate ourselves — each brief plan-vs-status-tagged so an investor can read intent and current reality side by side.
Research-design plan
Provider + patient discovery plan: literature-derived hypotheses, methodology, and the interview program ahead. (Pause is pre-design-partner; this is the research we'll run, not research we've run.)
Data inventory + strategy
Sources, integration order, moats, and the compliance posture (HIPAA today; HITRUST + SOC 2 Type II on the roadmap).
Competition
Six competitive categories, a capability matrix, and the differentiators that compound with deployment time.
Digital strategy
Five architectural pillars, GTM motion by year, the five moats, and operating principles. Every pillar tagged with current status (Shipped / Wired in prototype / Designed / Future).
Technology choices
Ten stack layers, six AI-approach axes, an evaluation framework, and a six-principle safety stance — each layer status-tagged and cross-linked to the architecture brief that owns it.
Arc B · Architecture + implementation
How Pause actually works (nine briefs)
Each architecture brief has a proto-vs-prod table, a phased plan, and a “Touch the architecture” section linking out to live mocked APIs and (where they exist) live demo pages. The five cards with a “See the demo” or “Live API” link below are observable today.
Agent Fabric
Multi-agent control plane: registry, policy catalog, trace plane. Anthropic Claude-backed Care Router runs here.
Salesforce Data 360
Unified patient memory: Identity Resolution + Calculated Insights + Segments, zero-copy federated over JupyterHealth + DBDP + EHR-of-record.
Agentforce intake
Live patient intake on a real Salesforce Service Cloud org today. The substrate our health-system customers already operate.
MuleSoft integration
Three-tier API-Led Connectivity (System / Process / Experience) stitching JupyterHealth, DBDP, and wearable feeds into a single FHIR substrate.
MCP server
Pause as a tool surface for AI agents — four MCP tools, copy-pasteable configs for Claude Desktop, Cursor, and Agentforce.
JupyterHealth integration
Which JupyterHealth pieces we adopt, in what phase order, and what we contribute back.
DBDP feature engineering
Wearable + biomarker features via the Digital Biomarker Discovery Pipeline. Phase 1 shipped: FLIRT-backed RMSSD with closed-form correctness tests.
Provider graph
A defensible menopause-clinician routing graph from CMS NPPES + state boards + taxonomy + outcomes. Closed-loop scoring that compounds with deployment.
Menopause Society partnership
Four paths to MSCP partnership with explicit guardrails on what we never claim. The advisory + credential moat.