Integrated Health Platform
Overview
Over four years I led end-to-end creative for Dario’s multi-condition platform—brand, product design/architecture, and film/content. The goal was a single experience that worked across diabetes, weight management, and hypertension, made outcomes obvious, and shipped faster. We consolidated patterns into a new design system, rebuilt onboarding, clarified the enterprise story around outcomes, and created a content pipeline that turned scripts into motion quickly. I also introduced AI assistants (PAIASTAR) to accelerate research, variant generation, and editorial polish.
What I owned
 - Cross-condition product design & product architecture
 - Design System v2 across app + web
 - Onboarding flows & member journey
 - Outcome-first web/story modules
 - Marketing B2B & B2C
 - Film/content pipeline: script → storyboard → motion

Summary 
Multi-condition (cardiometabolic, MSK, behavioral) platform. I led product design & architecture, marketing, brand system, and film/content—unifying journeys and outcomes across the experience.
Problem
Dario’s multi-condition platform (cardiometabolic, MSK, behavioral) had strong clinical results but a fragmented journey: inconsistent patterns across conditions, unclear enterprise story, and design debt slowing releases. We needed one system that made outcomes obvious, accelerated shipping, and read clearly for both members and enterprise buyers.
Constraints
Regulated healthcare, PHI/consent flows, clinical accuracy, multiple hardware devices, partner customization, distributed teams, aggressive roadmap.
Approach
Product & Architecture — Mapped cross-condition journeys, defined one IA, unified onboarding, and shipped Design System v2 (tokens, patterns, accessibility) across apps and web. Instrumented key events to measure onboarding and “stickiness” (DAU/MAU).
Brand & Story — Reframed the platform around outcomes; created a proof→UI→action story module used in web, decks, and in-product moments.
Content & Film — Directed product films and program explainers; built a content ops pipeline from script→storyboard→motion with channel-specific variants.
AI Assist (PAIASTAR) — Used role-based agents for brand voice, variant generation, and research synthesis to cut draft cycles.
Outcomes 
 - Onboarding completion +34% (old stats)
 - DAU/MAU “stickiness” +22% (old stats)
 - Time-to-ship −37% (old stats)
 - DS v2 adoption 100% in two quarters (old stats)
 - Program-page CTR +52%, bounce −19% (old stats)

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