RAG frameworks

Orchestration layers like LangChain and LlamaIndex connect LLMs to private data via vector databases and retrieval pipelines.

RAG frameworks provide the plumbing for production AI by bridging the gap between static models and dynamic enterprise data. These tools manage the entire lifecycle: ingesting PDFs or SQL tables, chunking text for embedding models like OpenAI's text-embedding-3-small, and indexing vectors in databases such as Pinecone or Milvus. By implementing sophisticated retrieval strategies (like hybrid search or parent-document retrieval), frameworks ensure the LLM receives the most relevant context to eliminate hallucinations and deliver grounded, accurate responses.

https://www.langchain.com