On a tennis court, Priyansh Agarwal had a question that went beyond winning or losing a point: what exactly happened during a shot, and could technology help a player understand it better? The national-level tennis player and Grade XII student decided to build his own answer. Drawing on his experience with sports technology and motion analytics, Agarwal developed TennEdge, an AI-powered motion-sensing system designed to help tennis players analyse aspects of their performance, including swing speed, accuracy, power and spin.
For Agarwal, the idea emerged from a problem he had experienced as a competitive player. While sports such as cricket have increasingly adopted technology to provide players with performance insights, he noticed fewer accessible technology-driven options for tennis players. “As a competitive tennis player, I constantly observed a major gap in the sport: getting objective, data-driven feedback is incredibly difficult for the vast majority of players,” Agarwal told The Tribune. The question eventually became the foundation for TennEdge. “Why shouldn’t all tennis players have access to the same kind of intelligence?” he said.
Agarwal's exposure to sports technology began during his internship at StanceBeam, where he learnt about intelligent sports wearables, motion-sensor systems and AI-driven performance analytics. According to his professional profile, the experience introduced him to sensor-data collection, data processing, hardware-software integration and the use of machine learning for generating sports insights. That experience encouraged him to explore whether similar technology could be adapted for tennis. The result was TennEdge, a motion-sensing system designed to capture aspects of a player's movement and convert them into measurable performance insights. The technology is intended to analyse parameters such as swing speed, shot accuracy, power and spin, with the data transmitted to a companion application through Bluetooth.
Developing the technology came with a practical problem. A tennis racket is highly sensitive to changes in weight and balance. Adding a device directly to the racket could potentially affect how it feels during play. Agarwal therefore explored an alternative approach: integrating the sensing technology into a wearable form that would be less disruptive to the player's natural movement. The idea reflects a larger challenge in sports technology — collecting useful performance data without interfering with the athlete's performance. For Agarwal, building the technology involved the same mindset he developed through tennis. “Tennis has taught me that performance is built through continuous iteration. You analyse what worked, identify what didn’t, make an adjustment and try again,” he said.
But the project also led Agarwal towards another question. Why do many students learn technical concepts in classrooms but get limited opportunities to actually build something with those skills? That thinking contributed to the creation of Skill Bridge, an initiative aimed at helping students connect with technical and vocational skill-development opportunities. According to Agarwal's profile, the initiative focuses on creating awareness about skill-development programmes and guiding young people towards certified training opportunities across technical and vocational fields. “The biggest gap I see is between learning technology theoretically and actually building with it,” he said. The larger goal is to encourage hands-on learning in areas such as electronics, embedded systems and other industry-oriented technologies.
Agarwal's journey combines several interests that do not always appear together in a typical school student's profile. He is a Grade XII student, national-level tennis player and Sports Captain at his school. His academic subjects include Physics, Chemistry, Mathematics and Computer Science, while his activities extend to tennis, music and technology clubs. His professional and technical experiences have also included a Sports-AI and Motion Analytics internship at StanceBeam and a Data Analytics internship involving the analysis of e-waste records. Through these experiences, he has explored how sensors, data analysis and machine learning can be used to convert raw information into practical insights.
Agarwal's ambition for TennEdge goes beyond elite athletes. “Accessibility is one of the core motivations behind TennEdge,” he said. “My vision is not to create a technology available only to elite athletes. I want young and amateur players to have access to meaningful performance data.” The immediate challenge is to take TennEdge from an innovation and prototype stage towards a robust and scalable product. At the same time, he hopes to expand Skill Bridge and help more students gain practical exposure to technical skills. For now, however, the story of TennEdge begins with a relatively simple question from a young tennis player: instead of merely wondering why a shot went wrong, could he build something that helped find the answer? For Priyansh Agarwal, that question moved from the tennis court into the world of sensors, AI and engineering — and eventually became an innovation of his own.
