Funding Fuels Expansion of Qdrant’s Open-Source Vector Database, Enhancing Scalability and Efficiency for Next-Gen AI Use Cases. BERLIN--(BUSINESS WIRE)--Qdrant, the leading high-performance, ...

Abstract: Retrieval-augmented generation pipelines store large volumes of embedding vectors in vector databases for semantic search. In Compute Express Link (CXL)-based tiered memory systems, ...

Create collections with configurable vector dimensions Store documents with their vector embeddings in Qdrant Search for similar documents using vector embeddings ...

As more AI systems become mission-critical for the agentic era and enterprise companies begin to adopt retrieval-augmented generation, also known as RAG, vector search has become the go-to for data ...

This is a self-hosted web UI for Qdrant Vector Search Engine. This UI is supposed to be served by Qdrant itself, but you can use it as a standalone application. Main goal of this UI is to provide a ...

Abstract: Retrieval Augmented Generation (RAG) is the de-facto technology used by pre-trained large language models to access data in databases, in addition to the data stored in their parameters.