Convenient and accurate nutrition analysis
Send an image – get nutrition information
Add nutrition analysis
to your product
Delightful user experience
Simply take an image of your food and get information on it’s nutritional content. No need to search through endlessly long lists of foods or to use a scale determine portion sizes. SNAQ’s simple web-API offers the complete solution to add nutrition analysis to your product.
Accuracy
Nutrition facts for Potatoes
- Kilocalories 180
- Fat 0.5g
- Carbohydrate 52g
- Protein 0g
Accurate analysis
Based on our patent pending technology SNAQ provides reliable food recognition, image based portion calculation and a well structured nutrition database supporting multiple regions. Our unique approach allows to conveniently and accurately determine the nutritional content of individual and mixed-foods in real-life scenarios.
Comprehensive features -
one integration
Food recognition
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.
Portion calculation
Sizing of individual food items and portion weight calculation based on our patent pending technology. No need for using a scale or estimating by eye.
Nutrition database
Well structured nutrition database supporting multiple regions. Unique selection options to determine nutrition facts of mixed foods. Extendable to use any pre-existing database.
Trial
Send a request- 1k requests
- Food recognition
- Portion calculation (limited)
- Nutrition database
- Attribution required
Professional
Send a request- 20k requests
- Food recognition
- Portion calculation (limited)
- Nutrition database
- Attribution required
Enterprise
Send a request- Custom number of requests
- Food recognition
- Text based food search
- Portion calculation (full)
- Nutrition database
- No attribution required
Great Partners
Diabetes Center Berne
The Diabetes Center Berne improves the therapy of people with diabetes mellitus by adressing unmet needs.
ETH Entrepreneur Club
The ETH Entrepreneur Club is a student association affiliated to the ETH Zurich. They bring entrepreneurial-minded people together and support them in the execution of their ideas.
be advanced
be-advanced ist die neue Innovationsagentur des Kantons Bern und unabhängiger Impulsgeber für Unternehmen zur Stärkung der Innovationskraft und Wettbewerbsfähigkeit der hier angesiedelten Unternehmen.
Venture Kick
Venture Kick is the largest startup accelerator in Switzerland. One can get support and pre-seed financing up to 130'000 CHF to kick a project.
Stiftung für technologische Innovation
Die Stiftung STI unterstützt den Aufbau von Unternehmen in der Region Bern. Sie fördert Unternehmer/innen in ihrer individuellen, frühen Entwicklungsphase.
Innosuisse
Innosuisse is the Swiss Innovation Promotion Agency. It is a federal entity under public law with a separate legal personality. Innosuisse’s role is to promote science-based innovation in the interests of industry and society in Switzerland.
Reveal the impact
of food on health
SNAQ reveals the impact of food on health. With our patent pending nutrition analysis solution we aim to provide the most convenient and accurate way to capture nutritional intake and explain how it affects different health parameters such as glucose or blood pressure. SNAQ GmbH offers their technology for licensing for health and lifestyle applications.
Aurelian Briner
CEO
Aurelian drove the strategy, design, development and roll-out of various software products in his previous job as Product Manager. He led the introduction of four products from idea to production building up his experience on mobile, machine learning, IoT and enterprise software topics. Aurelian holds a Bachelor's degree in Business Administration and a Master degree in Accounting and Finance.
Nico Prevtiali
CTO
Nico has over 5 years of professional software engineering experience. He holds a Bachelor's and Master's Degree in Computer Science from ETH Zurich. The focus of his studies was on data analysis and machine learning applied to visual computing.
Lukas Frischknecht
Computer Vision Engineer
Lukas holds a Bachelor's and Master's degree in Mechanical Engineering from ETH Zurich in which he focused on Robotics. He has acquired a wealth of experience in software development both in industry and academia. In previous projects he worked on versatile topics such as predictive maintenance of gas turbines, the localization and mapping of quadrocopters and the detection of repetitive architectural patterns in 3D reconstructions of buildings.
Michael Sladoje
Machine Learning Engineer
In previous projects Michael gained valuable experience in the fields of machine learning applied to image and audio data. In addition, he also worked on mobile and web development as well as test management. He holds a Bachelor degree in computer science from ZHAW and is finishing his Master degree in Data science at the same university.