If you run AI platforms for a bank, an insurer, or anyone else living under a stack of regulations, you already know the use case everyone asks for first: let our compliance and risk teams ask questions against our own policy documents and get an answer they can trust, with a citation they can check.Retrieval-augmented generation (RAG) is the right tool for that job. When a question is asked, instead of answering from memory, the model looks the answer up in your documents and includes a citation.The part slowing teams down isn’t the pattern, it’s the configuration. A RAG pipeline includes a n
Build a compliance assistant with AutoRAG and Red Hat OpenShift AI
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September 10, 2026
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