Qdrant API
Qdrant is a vector database designed for high-performance similarity search and machine learning applications, enabling businesses to build AI-powered search, recommendation systems, and semantic applications with fast vector operations.
Power AI-ready data operations with Qdrant API and Nexla. Our Qdrant API connector makes it simple to ingest, transform, chunk, and deliver structured or unstructured data to Qdrant API — all without coding. Nexla automatically organizes raw text and documents into reusable data products that you can easily prepare for vector search and retrieval-augmented generation (RAG) using our built-in transforms like agentic chunking and incremental loading. With real-time validation, schema checks, and comprehensive monitoring, Nexla keeps your Qdrant API workflows fast, secure, and fully governed for production AI use cases.
Features
Type: Vector Database
- AI-Ready Data Preparation: Automatically chunk, vectorize, and index data from any source into your vector database for fast, contextually relevant search
- Advanced RAG Integration: Query vector databases to power retrieval-augmented generation workflows with query rewriting, re-ranking, and multi-model orchestration
- Enterprise RAG Framework: Build production-ready RAG applications with built-in access controls, evaluation grading, and NVIDIA NIM hardware acceleration