Embedditor is an open-source software application designed to optimize vector search in Language Model applications. It uses advanced Natural Language Processing techniques to clean and enrich your embedding tokens, intelligently splitting or merging content for semantic coherence. This tool filters out irrelevant tokens like stop-words, saving up to 40% on embedding and vector storage costs while enhancing search results efficiency. Embedditor is deployable on local PCs or enterprise cloud/on-premises environments, providing optimal utility for users in the AI and Language Model related applications sectors, even those without a data science background. Users can install it directly from the repository or as a Docker image at no cost.