ARTIS Development offers FocusedON, an AI-powered platform that provides precise body composition analysis from standard smartphone or tablet images. By estimating body fat, muscle mass, and visceral fat with clinically comparable accuracy, it delivers instant results and trend visualizations for fitness centers, clinicians, and health‑conscious individuals, while integrating securely with health apps and electronic records.
Funding
Funding not disclosed
Founders
Product
Problem
Accurate body composition measurement typically requires expensive, specialized equipment and trained technicians, limiting accessibility for fitness centers, clinicians, and individuals seeking reliable health metrics. Inconsistent or imprecise data can hinder progress tracking, personalized training, and medical assessments.
Solution
FocusedON leverages artificial intelligence to deliver precise body composition analysis using standard imaging hardware, such as a smartphone or tablet camera. The AI model processes captured images to estimate metrics like body fat percentage, muscle mass, and visceral fat with clinically comparable accuracy. Results are presented instantly through a user-friendly interface, allowing users to monitor changes over time without visiting a lab. The platform also integrates with health apps and electronic records, enabling seamless data sharing for trainers, clinicians, and wellness programs.
Target Audience
Primary users include fitness centers, personal trainers, medical clinics, and health‑conscious individuals who require accurate, on‑demand body composition metrics.
Features
- AI-driven analysis of 2D images to calculate body fat, muscle, and visceral fat percentages
- Real-time results displayed on mobile and web dashboards with trend visualizations
- Compatibility with standard smartphone or tablet cameras, eliminating the need for specialized hardware
- API integration for health platforms, fitness apps, and electronic health record systems
- Secure data handling with encryption and user consent management