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Advanced RAG

Naive RAG retrieves once and hopes. DSN’s RAG graphs grade what they retrieved, rewrite the query, and try again before answering.

Corrective RAG drops irrelevant chunks. Self-adaptive RAG changes strategy when retrieval is weak. HyDE generates a hypothetical document to improve recall on sparse corpora.

Use this when the source is large, messy, or mixed (notes + tables), not when a single cached dataset will do.

What this does for the business

  • Answer policy and research questions against long document sets.
  • Reduce “I don’t know” and invented citations on sparse retrieval.
  • Pair with Agentic RAG when the question also needs a model or SQL tool.

API

POST /api/langgraph/rag

Full reference: api.dsnresearch.com/docs

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