Biomarker Platform

Problem

Biomarker and wearable data can be technically rich but hard for users to interpret. The platform needed to present health signals in a way that supports useful decisions without overwhelming people with raw data.

Approach

• Organized the dashboard around interpretation and action instead of raw metric volume.
• Separated data sources from the user-facing health story so integrations could evolve over time.
• Planned the experience around explainability, trend visibility, and clearer handoff between data and recommendations.

What shipped

• Unified dashboard concept for lab results, wearable data, and lifestyle inputs.
• Information model for making complex biomarkers easier to review and explain.
• Product direction for turning fragmented health signals into usable next steps.

Stack

Constraints handled

• Needed to make sensitive health signals useful without presenting unsupported medical certainty.
• Had to leave room for changing data sources, wearable feeds, and lab result formats.
• Required clear separation between data ingestion, interpretation, and user-facing recommendations.

Next proof to add

The next proof layer should include implemented integrations, security and data-handling posture, and practitioner or user workflow feedback.