Semantic Search by 📝TipTap is a feature that introduces AI-based search capabilities into collaborative document libraries. Released in limited beta for enterprise customers, it enables users to locate relevant content through contextual understanding rather than relying solely on keyword matching. The system employs large language models to generate vector embeddings of both queries and documents, allowing comparisons based on semantic similarity. This approach enhances retrieval accuracy, surfaces related ideas, and recognizes synonyms or varied phrasing. Semantic Search supports use cases such as knowledge management, document retrieval, and idea generation. It can also be paired with Retrieval-Augmented Generation (RAG) workflows, where contextually relevant documents are integrated into large language model outputs to improve the quality of AI-assisted content creation.
