Carb Counting, Simplified.

Snap a photo of your meal and instantly see carbs, protein, fiber, and calories.

SNAQ helps people, including those living with diabetes, connect what they eat to their blood sugar data.

⭐ 4.6 App Store · 1M+ meals logged · Connects with leading CGMs and Pumps

Help People Connect Meals and Glucose

Whether you use a CGM, a BGM, or neither, SNAQ helps you keep a clear diabetes food log with meaningful context.

People with:
Type 1 diabetes,
Type 2 diabetes,
prediabetes,
gestational diabetes

Anyone tracking glucose to understand how food affects their body

People who want faster, photo-based carb counting with clear trends and charts

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How It Works

Snap a photo of the meal and SNAQ counts Carbs and Macros

Snap a Photo, Get Carbs Instantly

Take a picture of your meal.

SNAQ’s AI carb counter recognizes foods and shows carbs, protein, fiber, fat, and calories in seconds.

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See How Meals Relate to Glucose

Connect SNAQ with your CGM, BGM or Insulin Pump.

You can visualize how each meal fits into your glucose trend and start noticing patterns that support your diabetes journey with confidence.

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Charts shows Glucose data from CGM after meal
Nutrition trends and meal logbook

Track Progress Over Time

Save meals, view nutrition summaries, and spot which foods work best for you.

Whether you’re learning or fine-tuning, SNAQ keeps it simple.

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Supports

SamsungApple WatchWithingsPolarGarminWhoop & More
Android currently only supports Dexcom, FreeStyle Libre and Contour. Inpen is only available in the US.

Backed by Research & Real-World Use

Independent studies have evaluated SNAQ’s meal-analysis technology, showing an average carb-estimation error around 5.5 grams in study settings.

Thousands of people use SNAQ every day to log meals, explore nutrition, and understand patterns.

6.6%

Improvement in Time-In-Range

C. D. Piazza, L. Kastrati, L. Bally, D. Herzig, C. Nakas. Efficacy of an image-based automated food analysis app in AID users with type 1 diabetes on glucose control: a randomised controlled trial

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5.5g

Mean absolute Carbohydrate estimation error

Herzig D, Nakas CT, Stalder J, Kosinski C, Laesser C, Dehais J, Jaeggi R, Leichtle AB, Dahlweid F, Stettler C, Bally L Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone

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42%

Adherence three months after app start

Latest internal data analysis Q4 2023. Adherence defined as people adding meals.

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Questions? We’ve Got You Covered.

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