DataStax Launches RAGStack, an Out-of-the-box Retrieval Augment Generation Solution, to Simplify RAG Implementations for Enterprises Building Generative AI Applications
DataStax , the company that powers generative AI applications with real-time, scalable data, today announced the launch of RAGSta ck , an innovative, out-of-the-box RAG solution designed to simplify implementation of retrieval augmented generation (RAG) applications built with LangChain.
- DataStax , the company that powers generative AI applications with real-time, scalable data, today announced the launch of RAGSta ck , an innovative, out-of-the-box RAG solution designed to simplify implementation of retrieval augmented generation (RAG) applications built with LangChain.
- RAGStack reduces the complexity and overwhelming choices that developers face when implementing RAG for their generative AI applications with a streamlined, tested, and efficient set of tools and techniques for building with LLMs.
- This removes the hassle of having to assemble a bespoke solution and provides developers with a simplified, comprehensive generative AI stack.
- “Every company building with generative AI right now is looking for answers about the most effective way to implement RAG within their applications,” said Harrison Chase, CEO, LangChain.