Open-source AI search engine
Fast Filtered Retrieval for AI Workflow Orchestration
Call Qdrant, the open-source AI search engine built in Rust, for real-time retrieval at any step of your workflow. Start free on Qdrant Cloud with no credit card.
AI system design
Better Retrieval Gives Your AI App Better Answers
Answer quality starts with retrieval. When the AI data layer returns the right context, the LLM has what it needs to answer well. Good AI system design treats retrieval as a first-class part of the architecture.
Plug retrieval into AI workflow orchestration.
Qdrant integrates with CrewAI, LlamaIndex, Haystack, LangChain, and AutoGen, so you can run retrieval as a step inside your agent loops and orchestrated workflows.
Design your payload schema with your application.
Store metadata next to each vector and filter on it at query time. Consistent payload fields keep filtering and ranking stable as retrieval requirements change.
Combine retrieval primitives at query time.
Mix dense vectors, sparse vectors, metadata filters, and multi-vector representations in one query, with explicit control over the relevance, latency, and cost of each.
OpenTable built Concierge, an assistant that answers restaurant questions in natural language, on Qdrant Cloud. Each query filters reviews, metadata, and other structured restaurant data at once, and the launch was global from day one, served from one deployment. Read the OpenTable case studyStart free with Qdrant Cloud
Workflow orchestration
Add Ingestion and Search Steps to Your Workflows
Your AI data pipeline already runs on a scheduler or a workflow builder. Add Qdrant as a step, and the run that generates new embeddings can also upsert and search them.
Schedule ingestion in Apache Airflow.
Install the official Qdrant provider and use its QdrantIngestOperator to upload vectors, IDs, and payloads from any DAG.
Query Qdrant from n8n and Make.
Use the official Qdrant node for n8n to manage collections, upsert points, and search for similar vectors, or add the Qdrant app to your Make (make.com) scenarios.
Deployment
Retrieval That Fits Your Stack
Qdrant is AI and ML infrastructure you can deploy where your data lives and plug into the tools your team uses.
Cloud deployment on your terms.
Run managed Qdrant Cloud with GPU indexing, or Hybrid Cloud in your own VPC.
See what your ML infrastructure is doing.
Qdrant exposes Prometheus and OpenMetrics metrics and works with Datadog and Grafana.
Build AI applications
Ground Your AI App in an AI Search Engine Open Source and Built in Rust
Build AI applications on Qdrant and give retrieval its own layer in your AI application architecture. Call that layer from any step that needs context. Retrieve context passages for RAG and agents. Give each customer their own results by filtering on the tenant ID in each point's payload.
Common Questions
How do I get started with Qdrant Cloud?
How do I build an AI application on Qdrant?
Where does Qdrant fit in AI workflow orchestration?
