Online education has gained widespread popularity due to its delivery of high-quality educational content, rich visual resources, and access to expert instructors. However, maintaining student engagement and comprehension in online classes remains a challenge. In response, we introduce a software that analyzes educational videos, designed to enhance students' understanding of these videos efficiently. We present Video Lens, a web application that leverages Natural Language Processing (NLP) and Computer Vision techniques, rooted in deep learning foundation models. It has four video analysis features: searching in video, transcription, summarization, and topic detection. We have found in the evaluation, involving students and teaching staff, the potential for Video Lens as a valuable educational tool. As a result, Video Lens has allowed us to let students test a tool for those who would like to efficiently use their time and efforts in studying their courses accompanied by video materials. This efficiency allows teaching staff to allocate more time to prepare and understand the content of lecture videos beforehand. These findings emphasize its potential to enhance the learning experience when engaging with lecture videos.