What Hybrid retrieval means in practice
Hybrid retrieval combines dense vector search (semantic similarity) with sparse keyword search (BM25 or similar) and fuses the results via Reciprocal Rank Fusion. The reason it works: dense retrieval excels on conceptual queries but fails on rare entities the embedding model never saw (drug names, regulation IDs, ticket numbers, customer codes); sparse retrieval excels on exact matches but fails on synonyms and paraphrases. Together they cover both failure modes. In MindMap's enterprise RAG deployments hybrid retrieval is the default — pure dense retrieval is reserved for narrow corpora where every term is well-represented in the embedding model's training data.
Related terms
Retrieval-Augmented Generation (RAG) →
A pattern where, instead of relying solely on the LLM's training, the system retrieves relevant documents from a knowledge base and includes them in the prompt as context.
Embedding →
A dense numeric vector representation of a piece of text (or image, or audio) such that semantically similar inputs produce vectors close in the embedding space.
Re-ranking →
A second-stage retrieval step where a more expensive model rescores the top-N initial results to surface the truly most relevant ones to the top.
Semantic search →
Search that matches on meaning rather than exact keywords, by comparing embeddings of the query and the documents.
More in this category
The Sovereign AI Playbook.
Enterprise generative AI that runs on your servers.
- 01Definition. The four non-negotiable properties of a sovereign deployment — and the three patterns that look sovereign but aren't.
- 02Why now. Three forces that converged in 2026: regulator pressure, the open-weights capability gap closing, and unit economics flipping.
- 03Reference architecture. The five-layer stack we deploy: applications → agent runtime → sovereign LLM → RAG + KB → data stores. With model and tooling choices for each.
- 04The regulators. SAMA · RBI · UK ICO · EU AI Act · DPDP · HIPAA — what each requires and how it maps to architecture.
All 62 terms, in plain language
Sovereign AI, RAG, agentic AI, IDP, MLOps and the regulations that shape enterprise AI.