Wellness
AI-Powered Wellness Platform
A privacy-first AI system integrating wearable biometrics, encrypted data architecture, and longitudinal modeling to generate context-aware, non-medical insights.
Longitudinal wellness scoring dashboard correlating biometric signals, structured dose tracking, and reflective journal inputs to surface context-aware, non-medical insights over time.
It All Started When...
Most wellness tools silo wearable biometrics, journaling, and structured dose tracking into separate experiences. Users experimenting with dosing protocols and wearable data lacked a unified system capable of identifying longitudinal patterns across physiological signals and lived experience.
The opportunity was to design a privacy-first AI platform that could securely ingest Oura Ring biometrics, structured dose logs, journal entries, and survey responses -- translating multi-dimensional inputs into responsible, non-medical insights.
Because the system handled sensitive health-adjacent data, encryption, row-level security, and governance-aware architecture were foundational requirements from day one.
Jaclyn's Role
Led product strategy for a privacy-first wellness platform combining biometric device integrations with encrypted data architecture.
Designed the AI-driven pattern recognition system that surfaces meaningful longitudinal health insights from noisy biometric data streams.
Architected row-level security and encryption frameworks ensuring sensitive health data remained private and compliant across all user interactions.
Defined NLP-powered insight generation features that translated complex biometric patterns into clear, actionable wellness recommendations.
Coordinated integration with multiple biometric API providers, establishing standardized data ingestion patterns across wearable devices.
Built experimentation infrastructure to continuously improve AI pattern recognition accuracy and user engagement with health insights.
Results
Delivered a production-ready v1 AI-powered wellness and dose tracking platform integrating wearable biometrics, journaling, and longitudinal modeling within a privacy-first architecture
Established encrypted data handling, row-level security, and responsible AI guardrails designed for sensitive health-adjacent use cases
Advanced the platform through MVP validation and architectural readiness, with launch paused pending privacy and regulatory considerations
Laid the groundwork for scalable AI feature expansion within a governance-aware framework
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