What it does
A vector database and vector search engine for AI search, semantic retrieval, filtering, and hybrid-search applications.
Why it belongs here
Retrieval infrastructure helps swap bloated prompts for targeted context windows by sending the most relevant chunks first.
Best use case
Production retrieval systems that need vector search, filtering, hybrid retrieval, and control over application-specific context.
How to use it
Index the knowledge base with useful metadata, retrieve narrowly, and track whether smaller context improves cost without hurting answers.
Limits
The database is one layer. Retrieval still needs good ingestion, ranking, permissions, and evaluation.
Tags
vector-dbsearchrag
