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SupportFit
Physical Wellness That Powers Performance
SupportFit, powered by Supportroom, is a comprehensive workplace wellness solution designed to improve employee movement, sleep, and nutrition. I led the end-to-end product design from scratch—defining user personas, backend physiological calculation logic (BMR, BMI, calorie burn rates), gamification loops, and seamless consultation flows.
Four foundational pillars architected into the system to guide employees toward sustainable wellness habits.
Continuous background synchronization with Apple Health, Google Fit, and smart wearables to automatically ingest daily steps, active heart rate, and sleep intervals.
Transforming raw biometric data into actionable progress summaries, highlighting metabolic burnout patterns and recovery deficit trends over rolling 7-day windows.
Direct chat, voice, and video interaction flows connecting employees with verified nutritionists and fitness specialists, with instant session scheduling and follow-ups.
Adaptive daily calorie deficit and hydration goals calculated dynamically using individualized BMR and BMI formulas rather than generic one-size-fits-all recommendations.
I worked at the intersection of product, UX, and systems logic, ensuring developers had precise state machines, data inputs, and interaction models.
- Collaborated closely with certified therapists to translate clinical and wellness requirements into intuitive product features.
- Restructured the end-to-end user journey, from initial wellness onboarding assessment to booking professional therapy sessions.
- Drove the V2 platform upgrade by identifying drop-off friction and introducing gamification mechanics (streaks, achievement badges, team challenges).
- Designed multi-channel communication tools including live chat, recorded voice notes, and automated session follow-up summaries.
- Architected the complete UI for the Resource Center, delivering curated exercise routines and mental wellness guides tailored to user goals.
System precision was key: every insight shown to users was backed by physiological data modeling and formula verification.
- Analyzed metabolic calorie burn rate algorithms factoring in multi-variable inputs: weight, height, biological age, and daily movement tiers.
- Implemented the Mifflin-St Jeor formula for Basal Metabolic Rate (BMR) and standard Body Mass Index (BMI) logic for baseline calibration.
- Helped formulate adaptive recommendation engines that adjust daily calorie allowances based on logged physical exertion.
- Conducted user testing sessions to eliminate cognitive overload during meal and water logging, streamlining the logging flow down to minimal taps without user friction.
My contributions transformed SupportFit from a static fitness checklist into a dynamic, data-driven wellness companion. By bridging biometric data models with compassionate interface design, employees gained an intuitive platform that fosters sustainable healthy habits and makes both mental and physical health support seamless to access.
Click any screen below to inspect the design tokens, typography, and micro-interactions in fullscreen view.
