Data & Knowledge Intelligence

Semantic Search

When people cannot find material because they do not know the exact words the author used, which is most of the time.

Semantic search matches meaning rather than keywords, over material where the searcher and the author chose different vocabulary. That gap is why keyword search feels broken to everyone except the person who wrote the document.

Access scoping matters as much as relevance: results must reflect what the searcher is entitled to see.

What the work includes

  • Embedding-based retrieval over your own corpus
  • Hybrid ranking combining semantic and keyword signals
  • Per-user access scoping applied to results
  • Relevance evaluation against real queries rather than synthetic ones
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When people recreate work that already exists because finding it costs more than redoing it.

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When answers must reflect your own current material rather than what a model learned during training, and every answer needs to be traceable to a source.

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As soon as retrieval moves beyond a prototype and the questions become which store, which embedding model, and how to chunk the material.

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Enterprise Knowledge Base

When the answer to most internal questions exists but is scattered across tools, and the people who know where to look are a bottleneck.

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// Common Questions

Questions
About This

Common questions about Semantic Search.

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Keyword search matches the words the searcher typed. Semantic search matches meaning, so a query about staff leave finds a document written about holiday entitlement. Most failed internal searches are vocabulary mismatches rather than missing material.

Not entirely. Exact matching still wins for identifiers, error codes, and product names, where the literal string is the point. Systems generally combine both, since each fails in the cases the other handles well.

Yes, when permissions are applied at query time so results are filtered to what the searcher could already open. Search that ignores this becomes a way to discover the existence of material people should not know about.

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