[Embedditor]

Effortlessly Edit LLM Embeddings with Simplicity of MS Word

121 followers

Effortlessly Edit LLM Embeddings with Simplicity of MS Word

121 followers

Embedditor is an open source Editor of vector LLM embeddings, which enables users to create impressive search results, improve performance of vector search, and save up to 30% on embedding and vector storage with the Simplicity of MS Word.

Free

Launch tags:Open Source•Developer Tools•Artificial Intelligence

Launch Team

Customer.ioAutomate Messaging Everywhere — Startups Get 12 Months Free

Promoted

Deepmark AI

Maker

📌

Hey Everybody, We are thrilled to open source Embedditor today. Embedditor is the open-source MS Word equivalent for embeddings that helps you get the most out of your vector search, while saving up to 30% on vectorisation and storage. Github : https://github.com/embedditor It's an innovative solution inspired by the experiences of over 30,000 IngestAI users. Our insights revealed a common bottleneck in AI and LLM-related applications, one that goes beyond LLM hallucinations or token limits, which are far easier to resolve. The prevailing issue lies in the GIGO (garbage in, garbage out) principle. With no one-size-fits-all approach to chunking and embedding, certain models excel with individual sentences, while others thrive on chunks of 250 to 500 tokens. Blindly splitting chunks by the quantity of characters or tokens, and embedding content without normalization and with up to 40% of redundant noise (such as punctuations, stop-words, and low-relevance frequent terms) often leads to suboptimal vector search results and low-performing LLM-related applications using semantic or generative search. The issue was consisting in trying to enhance vector search using existing technologies, which proved to be as challenging for our users, as creating an outstanding document using a basic .txt format. We decided to address the root problem, so we developed Embedditor - the Microsoft Word equivalent for embedding pre-processing, enabling with no background in data science or technical skills to improve performance of their vector search capabilities while saving up to 40% on embedding and storage. We've made Embedditor open-source and accessible to all because we genuinely believe that by improving vector search performance and boosting cost-efficiency simultaneously, Embedditor may have significant impact on current NLP and LLM industry. Hope you loved it. ❤️ and we would love to hear your usecases & feedbacks. 🙌

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3yr ago

@vasyl_r_ This open-source AI embeddings editor allows for faster and more accurate searches. The improved search capabilities of Embedditor are a dream come true for researchers and data analysts. The software is easy to use and the interface is intuitive, making it easy to get started.

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3yr ago

@vasyl_r_ Great product guys! Nice work! How big is your dev team out curiosity? Keep up the great work!

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3yr ago

Really cool and innovative self-hosted web application with a simple and minimalistic interface to search through your documents and communication with Openai based on different models!

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3yr ago

Deepmark AI

Maker

@andrew_vorobyov thanks a lot for your feedback, Andrew!

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3yr ago

That's super cool. Just yesterday we were discussing about embeddings editing issues at our company (Lastro)...

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3yr ago

Maker

@allan_paladino thank you so much for the feedback! Since launching IngestAI in February almost every day we faced our users' feedback that they want to have some ability to impact on embeddings. Since February we started working on Embedditor and hope this is a thing that can help the AI market a lot. That's why we decided to release it as an Open Source.

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3yr ago

Congrats for the amazing launch of this good project , i think this is gonna be brilliant especially this is an open source AI

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3yr ago

Maker

@jack_sofe thank you so much for your feedback! Yes, we're open source, and we're going to add more tech stacks soon

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3yr ago

I am so ready to utilize this and start saving that 30% on embedding and vector storage, during inflation such discounts are such a life saver.

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3yr ago

Maker

@rehema_mboka1 thank you so much! 30% is an average savings, in some cases they can reach even 70%!

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3yr ago

I looked because I was impressed by IngestAI. This new product looks also very intriguing, but tbh I have no idea what an embedding is or what vector search mean. So I guess this product is less mainstream/more technical than the previous one... Wish you a lot of success though!

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3yr ago

Cheers for open-sourcing a visual editor for vector embeddings, enabling an inexpensive, intuitive search that yields striking results and savings!

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3yr ago

Maker

@lilo_newman thank you so much for your support! Hope you love the product!

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3yr ago

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