EVEN is an app designed to seamlessly and efficiently solve the all-too-familiar moments of sitting around a restaurant after the meal, trying to decide how best to split the bill. As two college students who frequently found ourselves lingering around restaurants sorting out I-O-U's and what's-your-Venmo and wait-how-much-again, we wanted to create a seamless and efficient experience for dividing the tab.


Simply take a picture of the receipt (or enter in prices manually), link items to individuals, and the app will do all of the heavy-lifting.


Our first challenge was figuring out the most efficient way for a user to split a tab – we sought to build an app that would lead the user from start to finish in the fewest amount of clicks. While we wanted to provide the option for customization (whether in nicknames of the people splitting the bills or in the names of the items themselves), we decided that most users in a rush would want to just immediately enter in prices.

As a humble team of two – neither of whom have front-end mobile application experience – we had to make some compromises. Since neither of us were familiar with Swift, we focused on the interface prototype and the backend development of the app. Graphic assets and mockups were built in Adobe Illustrator and Sketch, then later imported into Keynote for the prototype and demo. On the backend, we incorporated OCR technology by using Tesseract, which is an open source learning engine that can recognize characters from images. We use this technology to process receipts for convenient use of the app without having to enter every single item.


We're hoping to continue EVEN beyond LA Hacks. In the upcoming months, we'll have to familiarize ourselves with Swift, as well as continue refining the user experience and interface.

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