Making big data easy to digest

WhatToOrder delivers a search response in less than 10 milliseconds, processing millions of metadata points across hundreds of thousands of menu items. By incorporating sophisticated search & filters, the app's analytics return valuable data to the food & hospitality industries.

The Challenge

When a former hedge fund analyst wanted to create a better search experience for finding restaurant dishes, he approached Generativ to build an app that could rival Google. To keep the user experience advertisement-free, the founder also sought to collect user data that would rival powerful research competitors like Nielson and Mintel.

As a consumer search engine, the app required a lightning-quick response from millions of data points. As a B2B data service, it needed analytics that would allow for the collection of large amounts of data, and swift, comprehensive analysis.

Our Approach

As with all our projects, we designed WhatToOrder with the capacity to scale. This meant creating a framework that allowed not only for rapid growth, but also for the agility to adapt with new market research, user feedback and ideas.

With the framework in place, Generativ focused on building an architecture that allowed for nearly unlimited data entry without sacrificing speed. Finally, through diligent research and an understanding of both user intent within the consumer market, and data priorities in the food industry, we built the app to allow for multiple feature sets—rivaling those of Google in breadth and speed.

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