IBM introduced a content-aware storage (CAS) architecture that integrates AI data processing directly into the storage layer. The approach targets retrieval-augmented generation (RAG) workflows by embedding document vectorization within the storage system, reducing the need for external preprocessing pipelines. CAS shifts a core RAG function, document embedding using large language model-based techniques, into storage infrastructure.













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