Haystack is an open-source AI orchestration framework from deepset for building production-grade LLM applications and agents. Developers install it with pip install haystack-ai and assemble pipelines from modular, composable components covering retrieval, generation, memory and tool use. Pipelines can branch and loop, giving control over multi-step decision flows, and they are serializable, cloud-agnostic and ready to run on Kubernetes with logging and monitoring support. The core framework is free, with community help available on Discord. Paid options sit around it: Enterprise Support with pricing based on company size, and a visual Enterprise Platform with a free trial.
Haystack fits Python developers, machine learning engineers and platform teams who want to build retrieval and agent systems without locking into a single model vendor. It connects to OpenAI, Anthropic, Mistral, Hugging Face, Weaviate, Pinecone, Elasticsearch and other providers, so components can be swapped as requirements change. Enterprise teams that need private engineering support, deployment guides and access controls can add the commercial layers on top of the same open-source base. Newcomers to NLP are welcome in its community, though building with it assumes comfort writing code.
Common projects include advanced RAG pipelines with hybrid retrieval and self-correction loops, AI agents that call tools in looping workflows, and multimodal apps that process images or transcribe audio. Conversational bots benefit from the standardized generator interface, which keeps chat logic consistent when the underlying model changes. Content generation engines can be built with Jinja-2 prompt templates matched to an editorial workflow. Teams also use it to move a proof of concept to production with the same building blocks, testing and deploying through unified tooling, and to inspect and debug every decision an agent makes.
