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CubeMarch

Led end-to-end product engagements across wealth management, healthcare, and pharma, combining research with clinicians/SMEs and close partnership with engineering and data science to ship AI-enabled workflows and XR prototypes. The work emphasized defining north-star workflows and success metrics, establishing explainable-AI trust patterns, and building scalable design-system governance to speed delivery.

Task

Lead end-to-end engagements across Wealth Management, Healthcare, and Pharma clients. Plan/run research with clinicians and operational SMEs; synthesize findings into priorities. Partner with engineering/data science to ship AI-enabled workflows and XR prototypes.

  • Strategy

    Define north-star workflows and success metrics (adoption, task success, time-on-task, trust). Establish XAI/trust patterns (rationale, uncertainty, reversibility) as a reusable product capability. Create scalable design-system governance to reduce rework and speed delivery.

  • Design

    Journey maps, service blueprints, end-to-end workflow redesigns. Explainable AI UX patterns (evidence panels, confidence cues, auditability, error recovery). Token-based design system (Figma variables, component library, accessibility annotations). AI/XR interaction prototypes (Unity/OpenXR/MRTK) where relevant.

  • Client

    Model Simulations LLC

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