Cut down on LLM expenses and optimize quality with a top-notch RAG cache

RAG-Buddy, developed by provides a smart patent pending cache that reduces the LLM context size, leading to higher answer quality and considerable cost savings for RAG architectures. With swift plug-and-play implementation, you can enjoy performance and cost benefits straight away without affecting your pipeline!

  • For text classification, benefit from up to 65% cost savings with a <1% quality drop.
  • For other use cases like RAG+Citation or Q&A, enjoy cost savings of up to 50%.
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Comparison with RAG Cache

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Benefit 1

Reduce costs

RAGCache decreases the context size, reducing the number of query tokens. Fewer tokens mean lower costs for either a hosted LLM or your own LLM.

Benefit 2

Improve Answer Quality

Smaller context size improves answer quality. This is laid out in the paper "Lost in the Middle" ([2307.03172] Lost in the Middle: How Language Models Use Long Contexts).

Benefit 3

Get faster response times

LLMs are faster with a smaller context because of reduced token processing time. Another result is the effect known as Attention Mechanism: In transformer architectures, attention is computed between all pairs of tokens. This operation is quadratic in time complexity concerning the number of tokens, which means a longer context could significantly increase latency.

Benefit 4

Effortless integrations

RAG-Buddy's RAG cache is designed as a proxy for your existing LLM. Integration is as easy as adding a couple of lines of code to your existing code base.

Benefit 5

Why yet another LLM cache

Exact match caches (like Redis or SQLite) work but have few hits. Semantic caches are hard to implement correctly and have a high risk of big mistakes. RAG-Buddy's cache addresses both problems with a unique and state-of-the-art solution.

Backed by Science RAG-Buddy was developed by scientists with a track record of many years in the NLP and ML space. The algorithm was developed in cooperation with the University of Athens.

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RAG cache is part of's RAG-Buddy, the ultimate game-changer toolbox for taking your RAG pipeline to the next level.

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We use our own products to ensure their effectiveness. By implementing RAG cache for our internal RAG pipelines, we have considerably decreased costs and improved response quality.

Dimi Balaouras, CTO,