RAG-Ready
Data formatted so it can be chunked, embedded, and retrieved cleanly by a retrieval-augmented generation (RAG) system.
RAG-ready data is structured and chunked in a way that works well with retrieval-augmented generation pipelines: consistent record boundaries, self-contained chunks (each one makes sense without surrounding context), clean metadata for filtering, and no embedded formatting noise. The goal is that an AI system can retrieve a chunk and use it correctly without extra cleanup.
Example
A glossary where every term is its own JSON record with a `short_def`, `definition`, and `related_terms` field is RAG-ready. A 40-page PDF with no internal structure is not.