This project addresses the pressing need within the AI research community at for an effective platform to facilitate collaboration and access to relevant expertise. Building upon previous efforts, we developed an advanced semantic search and document re-trieval system to connect AI researchers at Carleton University with problem owners seeking ethical AI solutions. Our approach leverages large language models, such as OpenAI’s text embedding model, to enhance search functionality and provide users with a context-aware search experience. By integrating state-of-the-art AI techniques, we aim to bridge the gap between problem owners and relevant expertise, fostering interdisciplinary collaboration and advancing ethical AI research. Results indicate improved search accuracy and relevance, enabling problem owners to efficiently discover and match with Carleton faculty based on their research work. The project’s conclusion underscores the importance of semantic search in driving collaboration and innovation in AI research, laying the groundwork for future advancements in the field.