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Azure AI Search Deep Dive

📚 RAG & Grounding 10 min 80 BASE XP

The Search Engine Behind RAG

Azure AI Search is the recommended search service for Foundry RAG implementations, supporting three search modes:

Search Modes

ModeHow It WorksBest For
Keyword (BM25)Traditional text matchingExact terms, codes, IDs
VectorSemantic similarity via embeddingsConceptual queries, natural language
HybridKeyword + Vector combinedProduction (best overall quality)
Semantic RankingAI reranker on top of resultsMaximum relevance accuracy

Index Architecture

{
  "name": "company-docs-index",
  "fields": [
    {"name": "id", "type": "Edm.String", "key": true},
    {"name": "content", "type": "Edm.String", "searchable": true},
    {"name": "contentVector", "type": "Collection(Edm.Single)",
     "dimensions": 1536, "vectorSearchProfile": "default"},
    {"name": "source", "type": "Edm.String", "filterable": true},
    {"name": "title", "type": "Edm.String", "searchable": true}
  ]
}
🎯 Pro Tip: Always use Hybrid search + Semantic Ranking in production. Hybrid search combines the precision of keyword matching with the conceptual understanding of vector search, and semantic ranking further reorders results for maximum relevance.
FOUNDRY VERIFICATION
QUERY 1 // 1
What search configuration provides the best RAG quality in production?
Keyword only
Vector only
Hybrid search + Semantic Ranking
Full-text search
Watch: 139x Rust Speedup
Azure AI Search Deep Dive | RAG & Grounding — Azure Foundry Academy