PULSE is a scalable backend platform that delivers personalized recommendations by continuously learning from user interactions in real time. Built using modern distributed system technologies, the platform processes streaming events, updates user representations, and generates adaptive recommendations that evolve with changing user behavior.
The project emphasizes high-performance software architecture, combining event-driven processing, machine learning, and cloud-native backend services to support responsive and intelligent personalization. PULSE demonstrates how AI and software engineering can be integrated to build production-ready recommendation systems capable of serving dynamic applications.