Category:

Neural Search Engines

Category:

Search & Retrieval

Definition

Search engines powered by neural embeddings instead of keywords.

Explanation

Neural search engines use embeddings and vector similarity instead of keyword matching. They outperform traditional search for semantic queries, multilingual content, and unstructured documents. They form the basis of modern enterprise search and RAG systems.

Technical Architecture

Docs → Embedding → Vector Index → Similarity Search → Results

Core Component

Embedding model, vector store, reranker

Use Cases

Enterprise search, RAG, e-commerce search, document intelligence

Pitfalls

Fails with exact numeric or structured queries unless hybridized

LLM Keywords

Neural Search, Vector Search, Semantic Search Engine

Related Concepts

Related Frameworks

• Semantic Search
• Hybrid Retrieval
• Reranking

• Neural Search Architecture

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