Nuvilab provides a vision‑AI platform that uses video and sensor data to automatically recognize food items, portion sizes, and consumer interactions in foodservice settings. The system delivers real‑time analytics on consumption patterns, nutritional intake, and operational efficiency through a secure dashboard and APIs, helping large foodservice operators and health‑focused enterprises optimize menus, reduce waste, and enable personalized health recommendations.
Funding
$6.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Foodservice operators and health institutions struggle to obtain real-time, AI-driven insights into consumer behavior and nutritional health, leading to suboptimal menu design, waste, and missed opportunities for personalized health interventions.
Solution
Nuvilab offers a vision‑AI platform that analyzes video and sensor data from foodservice environments to automatically recognize food items, portion sizes, and consumer interactions. The system generates actionable analytics on consumption patterns, nutritional intake, and operational efficiency, which can be accessed through a secure web dashboard or integrated via APIs. By providing continuous, automated monitoring, Nuvilab enables businesses to optimize menus, reduce waste, and support personalized health recommendations without manual data collection.
Target Audience
Primary customers are large foodservice chains, institutional cafeterias, and health‑focused enterprises that need data‑driven insights into eating behavior and nutrition.
Features
- Real‑time computer‑vision models that identify a wide range of food items and estimate portion volumes with high accuracy
- Automated nutritional profiling that maps recognized foods to macro‑ and micronutrient databases
- Dashboard visualizations of consumption trends, waste metrics, and health compliance indicators
- API and SDK for seamless integration with point‑of‑sale, kitchen management, and health‑tracking systems
- Edge‑compatible deployment options to process video locally, ensuring low latency and data privacy
- Continuous model improvement pipeline that incorporates client feedback and new food categories