What It Does?? This project focuses on building a Tiered Search System using Apache Solr, designed to improve search relevance by prioritizing results based on weighted fields. It ensures users get the most accurate and meaningful results when searching through large datasets. How It Works?? We implemented a custom Tiered Search Handler in Solr that categorizes searchable fields into different priority levels. By assigning relevance scores, the system enhances search ranking and precision. Additional features like highlighting, boosting, and debugging further refine the search experience. Technology Used: Apache Solr – For full-text search and indexing, providing high scalability. Docker & Docker Compose – For easy deployment and containerized setup. Zookeeper – To manage distributed indexing and ensure high availability. In future i am planning to : explore AI-driven search enhancements, integrating semantic search and NLP-based ranking to further improve search relevance.