The project’s goal is to develop an advanced search engine for Knowledge Sharing Sessions, transforming how people engage with video content. The innovative tool ensures a seamless and intuitive search experience, providing quick and efficient access to the most relevant data in video recordings. By leveraging technologies like speech-to-text (converting spoken words into written text), natural language processing (enabling computers to understand and interpret human language), and semantic search algorithms (which consider the context and meaning of words to provide accurate search results), the search engine delivers accurate results with timestamp links to pertinent video segments. Additionally, the system offers a summarization feature that extracts key points from 5-min text segments, enabling users to quickly grasp the main content without viewing the entire recording. The system conforms to open standards like BGE-large-en-v1.5, Mistral 7B V2, and Whisper-V3 in order to guarantee accuracy and precision. The integration of LangChain enhances search result relevance by prioritizing critical information. Extensive testing showed a 60% improvement in search efficiency compared to traditional methods. Overall, the project represents a significant advancement in semantic video search, offering a powerful and intuitive tool that enhances the search process and enriches the knowledge-sharing experience for users. The discovery has the potential to greatly enhance knowledge sharing and cooperation by making it simpler to obtain insightful information from Knowledge Sharing Session recordings.