Gymnasio is an AI-powered home fitness system that utilizes 3D body reconstruction through a standard webcam to track user movements and deliver personalized training programs. This technology eliminates the need for wearables, providing users with tailored workout feedback and performance statistics to enhance their fitness experience.
Funding
$60K 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
Existing digital fitness platforms often lack the ability to accurately track user movements and provide personalized feedback, hindering the effectiveness of remote training programs. Users are often required to purchase and use bulky wearable sensors for motion tracking. This creates a barrier to entry and limits accessibility for many individuals seeking to improve their fitness from home.
Solution
Gymnasio offers an AI-powered motion tracking solution that uses standard webcams to reconstruct a user's body in 3D and provide personalized feedback. The technology integrates anatomical and functional characteristics to deliver tailored guidance and valuable statistics. Gymnasio's solution is designed as a plug-and-play system, allowing easy integration into existing fitness platforms without requiring extensive code modifications. The platform analyzes user movements and provides corrections, tracks progress, and helps users understand their current fitness level.
Target Audience
Gymnasio primarily targets digital fitness platforms, including those offering yoga, physiotherapy, and general fitness programs, seeking to enhance user engagement and personalization.
Features
- 3D body reconstruction from standard webcam input
- Integration of anatomical and functional characteristics for personalized feedback
- Asana correction for yoga and other movement-based exercises
- Real-time motion tracking and analysis
- User dashboard with downloadable data for CRM integration
- Plug-and-play integration with existing fitness platforms via browser plug-in or API
- Edge computing to perform calculations on the user's device, avoiding data transfer
- Customizable feedback based on the platform's teaching style