Inspiration

Many nutrition buffs still pay human coaches in WhatsApp chats:
snap a meal photo → wait hours → get macros and costly advice.
I’d done it myself (and so had my friends) until the bill hurt.
So I asked: “What if AI could answer instantly, for almost zero cost?”
That pain point sparked ZOVO.life — a WhatsApp-style chat where an AI coach delivers real-time calorie tracking and personalised guidance.

What it does

  1. Chat like WhatsApp — I type or drop a meal photo.
  2. Instant analysisGPT-4o Vision estimates calories & macros.
  3. Personal coaching — The AI factors a 12-question onboarding quiz and my meal history to send tailored tips for the day.
  4. Progress dashboard — I see daily / weekly macro targets and streaks.

Result: the value of a human coach, 24 / 7, with zero overwhelm.

How I built it

Layer Stack & Tools
Code scaffold Bolt.new one-click template → Expo / React Native
Front-end Expo Router, TypeScript, NativeWind (Tailwind-like)
Back-end Supabase (Postgres, Auth, Edge Functions, Storage)
AI layer OpenAI GPT-4o Vision endpoint for meal photos
Hosting Netlify for the web build (https://zovo.life)
E-mail Resend for password reset & onboarding drip
DevOps GitHub Actions → Netlify CI/CD, Supabase migrations

Challenges I ran into

  • Zero dev background. My last coding was 15 years ago (plain HTML/CSS). React Native, Supabase—even Git—were all brand-new.
  • Five complete restarts. I deleted the repo and re-scaffolded Bolt.new five times because things kept breaking faster than I could fix them.
  • Architecture fog. Screens, services, Edge Functions—everything was a black box; I peppered Bolt with hundreds of micro-questions to inch forward.
  • Web build nightmare. Mobile ran in Expo Go, but the browser build refused to load image-upload functions; hours of CORS-header detective work finally solved it.

Accomplishments I’m proud of

  • Working full-stack MVP in a handful of late-night sessions, from blank screen to live site at zovo.life.
  • Solved every blocker solo, using Bolt for ~95 % of prompts and a pinch of ChatGPT near the end.
  • First real users—friends who used to pay human WhatsApp coaches—now log meals in ZOVO instead and love the instant feedback.

What I learned

  • Clear Bolt prompts = speed. Short, precise requests beat hours on forums.
  • Modern stack mental model. Expo ➜ Router ➜ React components ➜ Supabase Edge ➜ Netlify CDN finally “clicked.”
  • Guardrails matter. Pre-deploy env checks and strict TypeScript types save days of silent failure.
  • Biggest insight: if a marketing guy can ship AI photo analysis in React Native, thousands of non-coders can build their ideas too.

What's next for ZOVO.life

  • Release on App Store / Play Store with a RevenueCat paywall.
  • Sync with Apple Health & Google Fit for passive data import.
  • Add group challenges and streak badges to boost retention and community.

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