Video event retrieval is the process of identifying and extracting specific events or actions from a video collection based on a given query or description. Effective retrieval systems must adeptly manage the storage, indexing, searching, and delivery of such information. However, current approaches often focus on speed or accuracy, while user interactivity and scalability are not the most focused keywords. Therefore, this paper introduces PumpkinV2, an interactive video retrieval system with high precision and scalability. Capturing a visually balanced user interface, the system deployed a temporal-enabled visual-text association search pipeline with adaptive reranking methods. The retrieval results are enhanced by applying multiplicative and additive approaches in the integrated temporal algorithm. Furthermore, the system is built on top of a highly scalable vector database, combined with vector quantization, format-optimized data and a production-grade gateway web server. PumpkinV2 achieved outstanding results at AI Challenge HCMC 2024, an annual video event retrieval competition, with 94% accuracy during qualifying rounds and ranked top 10 amongst finalists, proving its capability of as a robust, scalable and highly interactive system for video event retrieval.