Mirror Vision Golf Coaching Application Redevelopment

Mirror Vision, a golf coaching application, experienced limitations in both user experience and technical performance as its user base expanded. The platform featured a cluttered interface that created a steep learning curve for new users, reducing engagement and limiting adoption among amateur golfers. At the same time, real-time video streaming suffered from lag and instability, which impacted the accuracy and usability of swing analysis.

The application also lacked advanced analytical capabilities. There was no support for AI-driven swing analysis or multi-camera functionality, which restricted the depth of feedback available to users. Subscription management and cloud storage systems were underdeveloped, preventing seamless scalability and limiting the platform’s ability to deliver a premium coaching experience.

A complete redevelopment of the Mirror Vision platform addressed both performance and functionality gaps. The solution introduced a redesigned user interface with a clean, intuitive layout that improved usability and reduced onboarding friction. Enhanced device connectivity was implemented using real-time streaming frameworks, enabling seamless pairing and automatic synchronization across multiple devices.

Advanced computer vision and AI models were integrated to deliver precise swing analytics. Technologies such as YOLO-based object detection and custom machine learning models enabled accurate swing detection, gesture recognition, and event sequencing. Multi-camera support allowed users to capture and analyze swings from multiple angles simultaneously, while synchronized playback tools provided deeper insights into performance and technique.