# Search-grounded generation

**Source:** https://promtable.com/glossary/search-grounded-generation

> Search-grounded generation is the LLM workflow where every output sentence is anchored to a retrieved source — the production pattern behind Perplexity, ChatGPT Search, Gemini AI Overview, You.com.

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Search-grounded generation is the LLM workflow where every output sentence is anchored to a retrieved source — the production pattern behind Perplexity, ChatGPT Search, Gemini AI Overview, You.com.

Search-grounded generation is the AI-search product pattern: user query → fan-out web search → retrieve N pages → LLM reads them → answer with inline citations to which source supports each claim. Differs from plain [[rag]] in three ways: (1) sources are live web pages, not static index, (2) the generation must explicitly attribute claims, (3) the UX surfaces sources prominently. Production challenges: latency budget (users see streamed answer in ~2s), hallucination prevention (no claims without source backing), source quality filtering (block low-quality sites), citation accuracy (claim → source mapping must hold), recency (favor fresh sources for time-sensitive queries). The dominant LLM-app pattern in 2026 for consumer-facing search products.

## When to use

- AI search apps.
- Any consumer Q&A surface.

## Common mistakes

- Generating before retrieval finishes — race condition produces ungrounded text.
- Trusting any cited source — adversarial / SEO-spam sources need filtering.

## Related terms

- [citation-extraction](https://promtable.com/glossary/citation-extraction)
- [rag](https://promtable.com/glossary/rag)
- [ai-search-engine](https://promtable.com/glossary/ai-search-engine)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/glossary/search-grounded-generation
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