This study aims to explore the construction and management of multilingual corpora for Chinese and foreign language management platforms. In response to the problems of uneven data quality, errors, repetition, and inconsistency in traditional research, this article proposes the use of word embedding models to improve the efficiency of constructing and managing multilingual corpora. Effective processing and analysis of multilingual text data can be achieved through word embedding models, supporting the needs of Chinese and foreign language management platforms for multilingual data. The purpose of this study is to improve the multilingual support capability and data quality of the Chinese and foreign language management platform, and to provide technical support and methodological guidance for the development of the platform. Research has shown that the multilingual alignment accuracy of a multilingual corpus based on word embedding models reaches 95.9%. By studying new methods for constructing and managing multilingual corpora, it can better meet the demand for multilingual data in Chinese and foreign language management platforms, improve platform performance and user experience.