Case Study: Semiconductor Chip Manufacturing Company achieves ML‑driven athlete performance insights and injury prediction with Softeq

Improving Athlete Performance With Machine Learning Powered Predictions

The customer, the world’s top microprocessor, processor, and semiconductor chip manufacturer, engaged Softeq to build an internal motion-tracking solution for teams working on pattern recognition and AI projects. They needed a trusted provider with deep mobile and firmware expertise to deliver an iOS app, handle part of the firmware development, and ensure secure BLE synchronization and massive data-pack processing.

Softeq delivered an iPad Pro app that syncs wearable trackers via BLE, uploads bulk datasets to the cloud through the Kinduct API, and applies machine learning to predict injuries and generate actionable player stats; the team also reinforced the BLE syncing process to prevent data abuse. Softeq completed the project on time and on budget with all required functionality, enabling coaches and medical staff to use AI-driven insights to improve athlete performance and support large-scale data processing.