Product & Technology
Reliable detection and recognition of multiple food items in real-life scenarios. The highlighting of each food item in the image enables unmet user experiences.
SNAQ’s patent pending technology reliably determines the portion size of food items based on an image. It achieved a carbohydrate estimation error of just 15% in a recent preclinical study on a broad set of meals.
Well structured nutrition database supporting multiple regions. Unique selection options to determine nutrition facts of various foods. Easily extendable with your pre-existing database.
How it Works
Snap a Photo
Simply take an image of your food and get information on its nutritional content. No need to search through endlessly long lists of foods or to use a scale to determine portion sizes.
Nutrition facts for white rice and chicken curry
- Kcal 251
- Fats 5.1g
- Carbohydrates 26.2g
- Proteins 23.9g
Get Nutrition Information
SNAQ not only recognizes the foods but also estimates the portion size. For even more automation the suggestions are personalized based on an individuals’ habits and common local foods.
Clients and Partners
Sanitas Health Insurance has over 800,000 insured persons. The SNAQ Food Scanner got integrated into the Sanitas Active App.
With 1.34 million insured in compulsory health insurance, CSS is the largest health insurer in Switzerland. In collaboration with CSS, SNAQ developed an iron deficiency prevention app.
Diabetes Center Berne
The Diabetes Center Berne improves the therapy of people with diabetes mellitus by adressing unmet needs.
The University Hospital Zurich is one of the largest hospitals in Switzerland and combines 44 clinics and institutes under one roof. In collaboration, we are conducting a food analysis study.
The bytes4diabetes Award is a competition initiated to promote innovation in the field of diabetes. Its one of the largest diabetes innovation prizes in Europe. In 2020, SNAQ won the first price.
NVIDIA Inception Program
NVIDIA Inception nurtures cutting-edge AI startups who are revolutionizing industries. This virtual accelerator offers go-to-market support, expertise, and technology for program members through deep learning training, exclusive Inception events, preferred pricing on hardware, and more.
Reveal the impact of food on health
It is our mission to reveal the impact of food on health. SNAQ’s patent pending and scientifically verified technology provides users the most convenient and accurate way to capture nutritional intake and helps to manage the impact of food on health through personalized insights and recommendations.
Aurelian drove the strategy, design, development and roll-out of various software products with up to 500k users in the past 7 years of his career. He built up experience in mobile, machine learning, enterprise and IoT software. Aurelian holds a Bachelor's degree in Business Administration and a Master's degree in Accounting and Finance.
Nico designed and built large scale software systems for more than 125k monthly users for the past 9 years of his life. He was educated as a professional software engineer and holds a BSc and MSc in Computer Science from ETH Zurich where he completed his studies with a focus on artificial intelligence.
Before joining SNAQ, Alexander founded a computer vision based fitness startup where he worked on business and engineering aspects. He holds a Master’s degree in Business Administration with a minor in Computer Science from the University of Zurich
Machine Learning Engineer
David holds a BSc and MSc in Computational Science and Engineering from ETH Zurich. His expertise and interests are in the field of Deep Learning and Computer Vision. Before joining SNAQ he worked as Research Assistant at ETH Zurich and at ABB.
UX Designer / Front-End Engineer
Fabian has 5 years experience in UX Design and Product Management plus 3 years in Software Engineering. He holds a Master’s degree in Digital Management from Hyper Island and Bachelor’s degree in Computer Science and Design from FHNW.