AI Food Scanner for Smarter Meals

Based in Incheon, South Korea, Nuvilab has developed the NutriVision AI scanner—an advanced food recognition and analytics system that works instantly and without manual input. 

Designed for cafeterias, hospitals, schools, and large dining facilities, NutriVision uses a combination of RGB color imaging, 3D depth sensing, and stereo vision to capture every detail of a meal in real time. 

It identifies food types, measures portions, and records what’s left uneaten—all without disrupting the serving process.

Inside the Technology

NutriVision’s strength lies in its vast food database of more than 20 million entries, allowing it to recognize a wide variety of dishes, including complex meals. Its AI-driven algorithms estimate portion volumes with precision while filtering out non-edible waste like bones or shells. 

This ensures that nutrition and waste data are accurate and reliable. The system’s ability to analyse food without contact makes it both hygienic and efficient, reducing the need for manual weighing or staff intervention.

Beyond Identification: Real-World Impact

NutriVision’s data insights enable kitchens and institutions to adjust serving sizes, reduce waste, and improve nutrition planning. By tracking both served and leftover portions, it supports evidence-based menu adjustments that can enhance dietary health while lowering operational costs. 

In addition, its waste measurement capabilities align with global sustainability goals, helping organizations minimize their environmental footprint.

The Big Picture

As food waste and nutritional challenges continue to affect both public health and the environment, Nuvilab’s NutriVision offers a scalable, data-driven solution. By merging AI, computer vision, and a vast food database, it transforms meal tracking into a precise, automated process. 

For large-scale dining operations, it is not just a technology upgrade—it’s a step toward smarter, healthier, and more sustainable food management.