Summary
- Analyse screenshots (Peloton stats, workout notes, meal photos)
- Chat naturally: "did chest and triceps today, 4x10 bench at 80kg" → logged
- Track everything: cardio, strength, meals, rehab exercises
- Give me personalised workout recommendations based on my patterns
Why I built this:
I didn't hate other apps - I just wanted something that fits my exact needs without extra features I'll never use. Something simple that lets me dump workout data however is easiest in that moment.
Screenshot my Peloton ride? Done. Quick chat message about my gym session? Done. No forms, no complicated menus, just log and move on.
It's free right now because I genuinely want to know if this approach works for anyone else or if it's just me.
Try it, break it, tell me what you think. -
- Model
- Free
- Build time
- About 1 week
NeonFit
AI fitness tracker that turns screenshots and voice notes into structured workout logs - built in 3 days for £27 using Lovable. No manual logging required.
Added January 21, 2026
https://neon-fit.lovable.appI wanted a fitness app built around MY routine
I do Peloton 2-3x a week, weightlifting, tennis on Sundays, and I'm managing shoulder rehab. Rather than adapt to how apps think I should track, I built one that works how I actually work.
What it does:
AI snapshot
Project insights
Auto-detected by AIAI fitness tracker that logs workouts from screenshots and voice notes, built in 3 days with Lovable for personalized, no-fuss fitness tracking.
- Monetization
- Free
- Build complexity
- About 1 week
- Target audience
- Fitness enthusiasts who want a personalized, simple way to log workouts and meals without manual entry or complex menus.
Problem solved
Existing fitness apps require adapting to preset tracking methods and often include unnecessary features, making logging cumbersome.
Key features
- Analyze screenshots from Peloton stats, workout notes, and meal photos
- Natural language chat logging for workouts and exercises
- Track cardio, strength, meals, and rehab exercises
- Personalized workout recommendations based on user patterns
Stack detected
Reproducible playbook
Focus on building a simple, user-centric logging system that accepts multiple input types like screenshots and chat. Leverage AI to parse natural language and images for seamless data entry. Start with core features and iterate based on user feedback.
AI-generated suggestions based on this project — not a statement from the founder.
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