RAG frameworks
RAG frameworks covers libraries for retrieval-augmented generation, where a model answers from documents it looks up.
In brief
RAG frameworks, in brief.
What it isRAG frameworks covers libraries for retrieval-augmented generation, where a model answers from documents it looks up.
Where it sitsOne of 11 categories in the Retrieval layer. Retrieval is how an AI system finds the right information at the moment it needs it: web search APIs, vector databases, full-text search engines, crawlers, and the frameworks that tie them into an answer.
What we track28 products, including Amazon Bedrock Knowledge Bases, AnythingLLM, Cognita, Contextual AI and Dify.
The products
28 products in RAG frameworks.
Each name opens a search for that product in our index.
ProductMakerIts own site
From our census of 2026-11-08. A product listed here is one that belongs in this category; the search answer says whether we have checked it.
Questions
RAG frameworks, answered.
What is RAG frameworks in AI infrastructure?RAG frameworks covers libraries for retrieval-augmented generation, where a model answers from documents it looks up.
Which layer of AI infrastructure is RAG frameworks in?RAG frameworks is in the Retrieval layer. Retrieval is how an AI system finds the right information at the moment it needs it: web search APIs, vector databases, full-text search engines, crawlers, and the frameworks that tie them into an answer.
Which products are in RAG frameworks?We track 28 products in RAG frameworks, including Amazon Bedrock Knowledge Bases, AnythingLLM, Cognita, Contextual AI, Dify, DSPy, FlashRAG and Graphlit. The full list is on this page.
Retrieval