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Luvo Mobile App

Developing a nutritionist for your pocket.

Luvo is revolutionizing the frozen food industry by creating nutritious, real meals that taste amazing. Each meal is crafted by a licensed nutritionist and showcases their mission to help people eat better, even when they’re in a hurry. We worked with Luvo to to bring this mission to a larger audience and create an experience that would help people make quick, informed decisions about their food.

Answering the question “Should I eat this?”

Our app experience answers the question that often stalls us in the grocery store: “Should I eat this?”. With one simple scan, Luvo CheckIt seamlessly translates complicated nutritional labels into a conversational insight that helps users make a smart choice.

Crafting content & visual design to keep users engaged.

It was essential to bring the vibrancy and playfulness of the Luvo brand to the app experience. We did this by incorporating color and iconography that is both functional and beautiful. The centerpiece of the app features a gradient result screen that quickly informs users about a food without needing to read. The vibrancy of the gradient also informs the whimsical illustrations and complements Luvo’s bright, dynamic food photography.

With the brand pillars of Luvo in mind, we developed a friendly nutritionist’s voice to guide users. From Daily Tips to scan results, this voice informs all the app’s content, making delightful experiences for users that vary from day-to-day and product-to-product. The voice is accessible, mindful, and reinforces Luvo’s mission that smart choices can be made easily.


legal & tone.

The FDA has dense guidelines about nutritional language. We had to balance the app’s friendly, human voice with the more formal FDA requirements to make sure we weren’t misleading consumers or being too formal in tone.

Hunting for the
right database.

To ground the app in real utility, we needed an API with concrete nutritional data and ingredients for thousands of products. Simply put, no crowdsourced API would do. After quite the hunt, we found a data provider that was big enough to feature info on the most common grocery items but also had the most technical, useful information for the app.

Bridging the
gap with math.

Although our API was rich with data, we needed to find an algorithm that could match the data points to the food categories and make sense of the information. Finding this algorithm allowed us to correctly map scan results plus contextualize many hard-to-categorize foods.