Zilniq

Zilniq’s mobile experience was built using React Native with Expo, enabling fast development and a smooth, consistent experience across iOS devices. This approach allowed us to focus on performance and usability while maintaining a scalable and modern mobile architecture.

A core component of the platform is its AI-powered nutrition engine, which interprets natural language inputs to automatically log meals, estimate calories, and identify nutritional patterns. Users can simply describe what they ate using text or voice, and the AI processes the information to generate structured nutrition data.

One of the main technical challenges was designing a system capable of reliably parsing everyday food descriptions and converting them into accurate nutritional insights. We addressed this by building intelligent data processing flows that transform conversational input into clear calorie and macro tracking.

By combining React Native, Expo, and advanced AI capabilities, we created an experience that removes the friction typically associated with nutrition tracking. The result is a lightweight yet powerful app that makes food logging effortless while helping users better understand their eating habits over time.