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Engine guide perplexity

Perplexity

Pure RAG answer engine: every response is grounded in cited sources.

Company
Perplexity AI
In VectorCite
Checked in the console where a Perplexity key is set, or with your own key.
Official docs
docs.perplexity.ai

How it works

Perplexity is purpose-built as an answer engine: every query triggers retrieval (no 'should I search?' decision). Default model is Sonar. Retrieval uses hybrid search (dense + BM25) over Perplexity's own crawled index plus a partnership-feed (Yelp, Brave, others). Sources are reranked and the top 5 are synthesized into a cited paragraph. Perplexity's Query Fanout feature decomposes complex queries into 3–5 sub-queries and aggregates citations across all, a behavior other engines now copy.

Signals it weights heavily

  • Query coverage + sub-query coverage
  • Citation density
  • Recency
  • Structural clarity (H2 + lists)
  • BLUF answers

How to optimize for Perplexity

  • Allow PerplexityBot explicitly in robots.txt.
  • Optimize for sub-query coverage: your page should answer the seed query AND its decomposed sub-queries.
  • Direct, factual style works best: Perplexity's reranker prefers concise direct answers over rhetorical setups.
  • Recency boost: re-publish evergreen pillar posts with updated dates every 6 months.

Check a page against a real AI answer

The free audit asks Claude your buyer’s question with live web search, shows the sources it cites, and says whether your page is one of them.

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