Whisk understands food, recipes and products.

Our algorithms process more than 15 gigabytes of recipe data daily. What do we do with this detailed metadata about recipes?

The creation of a seamless digital shopping list is just the start. Whisk maps ingredients to more than 140,000 store items, giving shoppers a streamlined path from recipe inspiration to food purchase.

Our food semantic processing allows Whisk to present market-leading relevant advertising based upon recipe type, ingredient, taste, nutrition and price.


Hyper-Relevant Advertising

Whisk’s ontology and semantic analysis of recipes allows us to deliver advertising based on ingredient, diet, allergy, nutrition, price, cuisine, time, taste, course, preparation methods, and more.

Ingredient Properties

Whisk complements recipe data with proprietary data sets on ingredient properties like cooking impact, flavour, perishability and nutritional information.

Machine Learning

When a user selects a recipe or a matched store product, our system learns from that user’s preferences and continually improves future recommendations.

Content parsing

Using Natural Language Processing (NLP), our technology automatically parses recipe content to deliver an intuitive and smart shopping list. Lists can be easily uploaded to online retailers, viewed on mobile devices, emailed or printed to take in store.


Whisk suggests store items -- and other recommendations like complementary dishes, wine or beer -- based upon individual preferences. Our system analyses users’ taste profiles, capturing individual preferences like product brand, price and dietary needs. Instead of sifting through 15 different brands of butter at the store, Whisk knows the shopper's preferred choice.

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