Eldan Galperin

Full-stack product engineer

AI wellness app · 2025–26

StayYoung

A live, AI-driven wellness app — owned end to end, from the member experience to Tovi, the in-app AI coach, to the platform behind it.

The problem

Wellness guidance is generic and easy to drop. StayYoung set out to deliver a personalised, conversational experience that meets people in Hebrew, on mobile, and adapts over time — answering their questions in the moment, not after a search. That meant building a real product, not a landing page.

What I built

  • Owned the full stack end to end — the member app, Tovi the in-app AI coach, and the subscription, billing, and funnel platform that runs the business side.
  • Built Tovi, the AI coach: scoped prompts, streaming Hebrew replies, per-member context persisted across MongoDB + MySQL, and guardrails that keep answers safe and on-brand.
  • Designed a Hebrew-first, RTL-correct UI system on React + Tailwind + shadcn that stays fast on a mid-range phone.
  • Modelled the data in PostgreSQL with row-level security and SECURITY DEFINER RPCs; auth, OTP, and notification flows run through Supabase Edge Functions.
StayYoung app — personalised home with challenge progress and daily tasks
StayYoung app — the course & content library
StayYoung app — time-boxed fitness challenges with day-by-day progress
StayYoung app — the recipe library, filtered by diet, time, and course

Impact

  • Live on the App Store and Google Play, with real members using it daily in Hebrew.
  • Tovi fields hundreds of member questions a week — 24/7, with hard cost and rate guardrails.
  • An RTL-first design system keeps the mobile experience fast and consistent.

Stack

ReactNext.jsTypeScriptSupabasePostgreSQL / RLSMongoDBMySQLEdge FunctionsNode.js / ExpressOpenAITailwind