Open-source MS Word equivalent for embedding.
Embedditor is the open-source MS Word equivalent for embedding that helps you get the most out of your vector search.
Embed like a pro: Improve your embedding metadata and embedding tokens with a user-friendly UI. Seamlessly apply advanced NLP cleansing techniques like TF-IDF, normalize, and enrich your embedding tokens, improving efficiency and accuracy in your LLM-related applications.
Uplevel your vector search: Optimize the relevance of the content you get back from a vector database, intelligently splitting or merging the content based on its structure and adding void or hidden tokens, making chunks even more semantically coherent.
Get better security: Get the full control over your data, effortlessly deploying Embedditor locally on your PC or in your dedicated enterprise cloud or on-premises environment.
Reduce your costs: Applying Embedditor advanced cleansing techniques to filter out from embedding irrelevant tokens like stop-words, punctuations, and low-relevant frequently words, you can save up to 40% on the cost of embedding and vector storage while getting better search results.
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