If you shop on a mobile Device, you don't want to search around -> you just want all the ingredients for your recipe.

What it does

It compares the Product you put in your basket with well rated recipes over the API from spoonacular . Out of that it predicts what you want to buy next from the different categories. You put Toast Bread and Cheese in your basket so it might guess Ham and Pineapple for Toast Hawai. It presents you those ingredients as a recommendation. So you complete your basket much faster.

How we built it

We worked with the Data form the HelloFresh Data Challenge. We translated them and enriched them with Data from the USDA National Nutrient Database. Scraped nutrition data from the MyFitnessPal site to have a bigger database We took most liked Recipe Data over spoonacular API. We didn't have enough time to build the whole Front End, so we improvised and built a Mockup.

Challenges we ran into

HelloFresh Data Challenge(link):

  • different languagues -> API Translation
  • enrich the Data with the USDA National Nutrient Database -> complicated structure
  • parse the Data Sets, get the meaning from 3 Word ingredients

Spoonacular API (link)

  • get the right most liked recipies
  • match them with the chosen ingredients of the user

Lidl Challenge (link)

  • How to generate a better UX for mobile shopping

Accomplishments that we're proud of

  • improve the Hello Fresh Data Set
  • idea for better mobile shopping experience
  • combine it with available resources

What we learned

  • how to work with difficult data Sets
  • how to enrich data
  • show a nice UX over a mockup

What's next for vollkorntoast

Eat Toast-Hawai

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