Welcome to VectorSearch
VectorSearch (VS) is a self-optimizing hybrid indexing system for scalable and memory-efficient vector retrieval.
Features
- Quantization-based candidate filtering
- Lightweight graph refinement
Start with Getting Started
System Design Overview
VectorSearch (VS) introduces a modular architecture that integrates:
- Semantic embedding alignment
- Multi-vector query support
- Caching and memory mapping
- Dynamic hyperparameter tuning
The system executes a coarse-to-fine retrieval pipeline, leveraging quantized vector search for rapid candidate selection, followed by graph-based reranking for refined accuracy. This design enables high recall with minimal latency and adapts to diverse workloads without index reconstruction.
VectorSearch (VS) System Architecture
