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Bitewise is built off of layered API's to deliver immediate value to the user, with the use of pre-trained machine learning models specific to food that help identify the ingredients of any food from just a picture.
Before Bitewise, there was no convenient way to derive specific products from something as simple as a picture. If you went out to eat and saw an interesting dish you wanted to make later, or even saw something on social media, you had no practical way of figuring out what went into making it.
In fact, students spend in excess of 11 billion dollars going out to eat every year. Preprepared food vendors can charge markups of up to 300%. If only there was a solution that helped people to eat healthier, spend healthier, and live wealthier.
You can see the app at bitewise.club. It is super simple to use. All the user needs to do is upload a photo, and Bitewise handles the rest.
Image bytecode data is first stored in Google Firebase, where the hosted url is then passed into Clarifai's food recognition API. The output of that is refined through Spoonacular's product data API asynchronously to offer specific product recommendations and reference prices which are dynamically summed according to selected products.
In the future, as we scale, we could continue to layer API's to retrieve specific products or even train a more granular machine learning model that recognizes brands (or at least more popular ones).
In addition, Bitewise would benefit greatly under a partnership with big grocery chains like Walmart or Whole Foods, and could provide even more accurate and relevant data with access to developer and/or internal API's.