MetricSync
Cheaper than CalAI with more features and better accuracy
3 followers
Cheaper than CalAI with more features and better accuracy
3 followers
MetricSync is an AI nutrition tracker for iPhone that turns food photos into calories and macros fast. Compared with CalAI, it is cheaper, gives you more features, and aims for better accuracy with diabetes-aware workflows, macro tracking, and photo-based logging. New users get a 3 day free trial, then website checkout starts at $5/month.
This is the 2nd launch from MetricSync. View more
MetricSync
Launched this week
MetricSync is an AI nutrition tracker for iPhone built for people who want food logging to take seconds, not minutes. Snap a meal photo, scan a barcode, track calories and macros, and correct messy estimates fast. Compared with CalAI, it is cheaper, gives you more features, and focuses on better day to day accuracy. Includes diabetes-aware workflows and a 3 day free trial.
Free Options
Launch tags:Health & Fitness
Launch Team
Built this because I wanted food logging to feel faster than opening MyFitnessPal and less expensive than CalAI. MetricSync lets you log from a photo, scan barcodes, track macros, and it also has diabetes-aware workflows. We priced it at $5/month, there is a 3 day free trial, and we have been obsessive about accuracy so the photo logging is actually usable day to day. Happy to answer questions or run side by side comparisons if anyone here is testing CalAI alternatives.
Solo dev lesson from building MetricSync: the hard part was not getting an AI model to guess calories from a perfect photo. The hard part was making logging still feel trustworthy when the meal is messy, mixed, or half eaten.
That pushed me to focus on fast correction loops, barcode fallback, macro tracking, and diabetes aware workflows instead of chasing flashy demos. If an estimate is slightly off but easy to fix, people keep using the app. If it feels brittle, they churn.
That is also why we kept pricing simple at $5/month and added a 3 day free trial. I wanted something cheaper than CalAI, but only if it was actually useful day to day.
Curious what matters more to people here with AI nutrition apps: first guess accuracy or how fast you can correct the log when the guess is wrong?
One thing I learned building this is that better accuracy in AI nutrition tracking is not just about the first estimate.
It is about how fast someone can fix the estimate when the meal is messy.
A lot of apps look great on a clean demo meal. Real life is leftovers, sauces, takeout bowls, and random Tuesday lunches.
That is the standard I kept coming back to with MetricSync. If the log feels wrong, trust drops fast. If correction is easy, people keep using it.
If you have tried other AI food trackers, I would love to hear what usually breaks trust first for you.