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Fastest Food Recognition & Nutrition API
Photo in. Macros out. One API call.
β‘ Powered by our proprietary Vision AI β fine-tuned on 150,000+ dishes across global cuisines. π Full ingredient breakdown with individual weights & macros on PRO plans. π Expanded nutrient database for deeper, more reliable data. β Mathematically verified outputs β macro numbers always add up. Same simple API. Way smarter results.
A couple of years ago I was building a small app to help me track what I eat. Nothing fancy β just something personal to stay on top of my diet.
I needed a food recognition API. Seemed simple enough.
It wasn't.
Everything I found was either way too expensive for a side project, returning wildly inaccurate data, or so poorly documented I gave up after 20 minutes. I just wanted to point a camera at my lunch and get calories back. That's it.
So I built it myself.
Months of experimenting, iterating, and way too many late nights later β CaloAI was born. Trained on 150,000+ dishes, powered by our own proprietary Vision AI, with mathematically verified outputs so the numbers actually make sense.
I put it on RapidAPI because I figured if I struggled to find this, other developers probably did too.
If you're building a fitness app, a calorie tracker, a smart food diary β I hope this saves you the months it cost me.
Would love to hear what you're working on π
About Fastest Food Recognition & Nutrition API on Product Hunt
βPhoto in. Macros out. One API call.β
Fastest Food Recognition & Nutrition API was submitted on Product Hunt and earned 10 upvotes and 1 comments, placing #29 on the daily leaderboard. β‘ Powered by our proprietary Vision AI β fine-tuned on 150,000+ dishes across global cuisines. π Full ingredient breakdown with individual weights & macros on PRO plans. π Expanded nutrient database for deeper, more reliable data. β Mathematically verified outputs β macro numbers always add up. Same simple API. Way smarter results.
On the analytics side, Fastest Food Recognition & Nutrition API competes within Health & Fitness, API and Artificial Intelligence β topics that collectively have 652k followers on Product Hunt. The dashboard above tracks how Fastest Food Recognition & Nutrition API performed against the three products that launched closest to it on the same day.
Who hunted Fastest Food Recognition & Nutrition API?
Fastest Food Recognition & Nutrition API was hunted by Ivan. A βhunterβ on Product Hunt is the community member who submits a product to the platform β uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Fastest Food Recognition & Nutrition API including community comment highlights and product details, visit the product overview.
Ivan
Hey Product Hunt! π
A couple of years ago I was building a small app to help me track what I eat. Nothing fancy β just something personal to stay on top of my diet.
I needed a food recognition API. Seemed simple enough.
It wasn't.
Everything I found was either way too expensive for a side project, returning wildly inaccurate data, or so poorly documented I gave up after 20 minutes. I just wanted to point a camera at my lunch and get calories back. That's it.
So I built it myself.
Months of experimenting, iterating, and way too many late nights later β CaloAI was born. Trained on 150,000+ dishes, powered by our own proprietary Vision AI, with mathematically verified outputs so the numbers actually make sense.
I put it on RapidAPI because I figured if I struggled to find this, other developers probably did too.
If you're building a fitness app, a calorie tracker, a smart food diary β I hope this saves you the months it cost me.
Would love to hear what you're working on π