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CONCEPT Cited by 1 source

Metadata boost

Definition

Metadata boost is a query-time ranking adjustment that nudges results up or down based on document metadata values (recency, priority, region, language, tenant, …) on top of the underlying relevance score produced by retrieval + fusion + optional reranking. The relevance score is what could match the query; the metadata boost is what should be surfaced first among those matches given business / user context.

Named in Cloudflare AI Search (2026-04-16)

"Retrieval gets you relevant results, but relevance alone isn't always enough. For example, in a news search, an article from last week and an article from three years ago might both be semantically relevant to 'election results,' but most users probably want the recent one. Boosting lets you layer business logic on top of retrieval by nudging rankings based on document metadata."

— (Cloudflare, 2026-04-16)

Surface:

const results = await instance.search({
  query: "deployment guide",
  ai_search_options: {
    boost_by: [
      { field: "timestamp", direction: "desc" }
    ]
  }
});

timestamp is built into every item by default; any custom metadata field declared at indexing time can also drive a boost.

Why not fold into the relevance score

  • Separation of concerns. Retrieval scoring (BM25, vector similarity, fusion, reranking) is about what the text / embedding says. Metadata-driven ranking is about what the world says (time, priority, tenant). Keeping the axes separate keeps each debuggable.
  • Per-query overridability. The same corpus with the same index can be ranked differently per caller — recency for a news search, priority for a support ticket, region for a multi-tenant SaaS — without re-indexing.
  • Avoid the need to re-train or re-embed. Metadata changes (priority flipped, new timestamp) are cheap writes; baking them into relevance would require re-embedding or re-weighting the lexical index.

Shape

  1. At indexing time, attach metadata fields to each item.
  2. At query time, specify boost_by: [{ field, direction, … }].
  3. Retrieval + fusion run as normal; the engine applies the boost(s) to the resulting ranked list before returning.

The boost is an additional ranking signal, not a filter. Items without the metadata field are not removed — they just don't participate in that signal. Contrast with the other kind of "hybrid search" (vector-similarity + metadata predicate) where the metadata acts as a filter.

Seen in

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