Qdranthybrid searchenterprise RAGvector database
Vector-only is rarely enough
Enterprise corpora mix structured identifiers, acronyms, and natural language questions — vector-only search often misses exact matches.
Hybrid retrieval combines keyword and semantic signals with tunable weights per collection.
Metadata filters enforce tenant, region, and permission boundaries before ranking.
Qdrant in production architectures
Qdrant supports filtered vector search at low latency — valuable for multi-tenant SaaS with strict ACL requirements.
Collection lifecycle policies should version embeddings when source documents change materially.
Reranking layers recover precision when first-stage recall is intentionally broad.