RAG with Open-Source LLMs: Why You're Paying Too Much to Hand Your Data to Someone Else
(Antonio V. Franco) Every time someone asks me whether it’s worth using GPT‑5.5 or Opus 4.7 in a RAG pipeline, I ask them the same question back: would you trust your most sensitive documents to a foreign company that’s subject to the CLOUD Act? The answer, almost always, is an uncomfortable silence. Commercial models are good. Really good. But RAG is, by definition, an operation that involves sensitive data (internal documents, contracts, customer histories, regulatory information) flowing through infrastructure you don’t control. Every query your system makes to the OpenAI or Anthropic API carries the retrieved context and the generated response along with it. And that context, almost all the time, contains exactly the kind of information that data protection regulations are trying to shield. ...