Haystack
by deepset
Open-source Python framework for production RAG, search, and agents
Last reviewed 2026-06-19
Haystack is an open-source Python framework from deepset for building production LLM applications: retrieval-augmented generation (RAG) pipelines, agents, semantic search, and multimodal apps. Its 2.x architecture wires typed, explicitly connected components into a directed-graph pipeline runtime (with cycles for agent loops), giving developers fine-grained control over retrieval, routing, memory, and generation. It is a developer framework, so autonomy is whatever you build; Haystack apps span retrieval assistants and supervised, tool-using agents. The core is Apache-2.0 and free to self-host, backed by deepset's commercial Enterprise Platform. deepset has raised significant venture funding.
What it can do
Build RAG and retrieval pipelines
AssistantModular, typed components for retrieval, routing, and generation with explicit, inspectable data flow.
sourceBuild agent workflows
SupervisedCyclic pipelines and agent components support tool-using, looping agents bounded by developer logic.
sourceRun semantic and multimodal search
AssistantEmbedders, rerankers, and multimodal components power semantic and hybrid search applications.
sourceDeploy pipelines to production with observability
SupervisedPipelines deploy as services with tracing and monitoring integrations, and an enterprise platform for managed operations.
source
Strengths
- +Mature, explicit, production-oriented architecture with deep RAG and search heritage
- +Broad integrations and an Apache-2.0 license, free to self-host
- +Backed by an established vendor (deepset) with an enterprise tier
Limitations
- −Python-only
- −The component and pipeline model has a learning curve versus lighter agent SDKs
- −Agent abstractions are newer than the RAG core; the deepest production features sit in the paid platform
Overview
Haystack is deepset's open-source Python framework for production LLM applications. Its 2.x architecture (a 2024 rewrite) models apps as directed graphs of typed, explicitly connected components, which gives developers precise control over how retrieval, routing, memory, and generation fit together.
What it does
You build pipelines for RAG, semantic and hybrid search, and multimodal apps, and use cyclic pipelines plus agent components for tool-using, looping agents. Everything is explicit and inspectable, which suits teams that want control rather than magic. Pipelines deploy as services with tracing and monitoring. Because it is a framework, autonomy is developer-defined; most builds are retrieval assistants or supervised agents.
Integrations & setup
Model-agnostic across OpenAI, Anthropic, Google, Cohere, Hugging Face, and local models via Ollama. Vector and search backends include pgvector, Qdrant, Weaviate, Milvus, Pinecone, and Elasticsearch/OpenSearch. There is an official MCP integration. Install the Python package and self-host, or use deepset's enterprise platform.
Pricing
The core is Apache-2.0 and free. The Haystack Enterprise Platform is sold on subscription and enterprise terms.
Traction
deepset was founded in 2018 in Berlin and has raised tens of millions in venture funding (a Series B in the ~$30M range per public reporting), with investors including Balderton Capital and GV.
Best for / not for
Best for Python teams building production RAG, search, or agent systems who value explicit, controllable pipelines and an enterprise option. Less suited to JavaScript shops or those wanting the lightest possible agent SDK.
Alternatives
LlamaIndex is the closest data and RAG-centric peer; LangChain and LangGraph are broader; Dify offers a more no-code platform approach.
What people are saying
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FAQ
Is Haystack free?+
The core framework is open-source under Apache-2.0 and free to self-host. deepset sells the Haystack Enterprise Platform (formerly deepset Cloud) on subscription and enterprise terms for managed production use.
Is Haystack just for RAG?+
RAG and search are its heritage, but Haystack 2.x adds cyclic pipelines and agent components for tool-using agents, plus multimodal support. It is a general LLM application framework that happens to be especially strong at retrieval.
Sources
- Haystack overview (intro) · accessed 2026-06-19
- Haystack documentation (intro) · accessed 2026-06-19
- deepset-ai/haystack on GitHub · accessed 2026-06-19
- deepset (company) on Wikipedia · accessed 2026-06-19
Last reviewed 2026-06-19