Haystack
by deepset
Open-source NLP framework for building production-ready AI search and QA systems
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About
Haystack is an open-source LLM orchestration framework developed by deepset, designed for building production-grade NLP applications. It specializes in retrieval-augmented generation (RAG), question answering, document search, and conversational AI systems that need to work reliably at scale in enterprise environments.
Haystack provides a pipeline-based architecture where developers can mix and match components — document stores, retrievers, readers, generators, and rankers — to build custom NLP workflows. It integrates with all major vector databases (Pinecone, Weaviate, Elasticsearch, OpenSearch), LLM providers (OpenAI, Anthropic, Hugging Face), and document formats.
Used by enterprises across industries including finance, healthcare, legal, and technology, Haystack excels at building internal knowledge bases, regulatory compliance tools, and customer support systems that need to accurately retrieve and synthesize information from large document collections.
Haystack provides a pipeline-based architecture where developers can mix and match components — document stores, retrievers, readers, generators, and rankers — to build custom NLP workflows. It integrates with all major vector databases (Pinecone, Weaviate, Elasticsearch, OpenSearch), LLM providers (OpenAI, Anthropic, Hugging Face), and document formats.
Used by enterprises across industries including finance, healthcare, legal, and technology, Haystack excels at building internal knowledge bases, regulatory compliance tools, and customer support systems that need to accurately retrieve and synthesize information from large document collections.
Product Features
- Pipeline architecture for composable NLP workflows
- RAG (Retrieval-Augmented Generation) out of the box
- Integration with 10+ vector databases
- Support for OpenAI, Anthropic, HuggingFace, Cohere, and more
- Document processing: PDF, Word, HTML, CSV ingestion
- Evaluation framework for measuring answer quality
- REST API server with Swagger documentation
- Annotation tool for labeling question-answer pairs
- Docker and Kubernetes deployment support
- RAG (Retrieval-Augmented Generation) out of the box
- Integration with 10+ vector databases
- Support for OpenAI, Anthropic, HuggingFace, Cohere, and more
- Document processing: PDF, Word, HTML, CSV ingestion
- Evaluation framework for measuring answer quality
- REST API server with Swagger documentation
- Annotation tool for labeling question-answer pairs
- Docker and Kubernetes deployment support
About the Publisher
deepset was founded in 2018 in Berlin, Germany, by Milos Rusic, Malte Pietsch, and Timo Möller. The company has raised over $30 million in funding and operates with a remote-first team across Europe and the Americas. deepset also offers Haystack Cloud, a managed platform for deploying Haystack pipelines without infrastructure management. The company is a major contributor to the open-source NLP ecosystem and has been recognized as a key player in enterprise search and document AI.