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Cache-Augmented Generation

When the same dataset is queried all day, retrieving context on every call wastes tokens and time. Cache-augmented generation keeps a compiled snapshot of the data next to the prompt.

DSN builds dataset context once, then serves repeat questions from that cache instead of running a full retrieve-and-rerank pass.

That is the right default for operational dashboards, analyst chat, and agent loops that keep asking about the same source.

What this does for the business

  • Cut LLM spend on high-frequency questions against a stable dataset.
  • Keep interactive chat snappy enough for a live sales or ops meeting.
  • Use RAG when the corpus changes; use CAG when it does not.

API

POST /api/ai/cag

Full reference: api.dsnresearch.com/docs

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