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Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
End-to-end LLM framework for building production-ready RAG applications
Haystack orchestrates LLMs, embedding models, and vector databases into customizable pipelines for retrieval-augmented generation, semantic search, and question answering applications.
Haystack is an end-to-end framework for building applications powered by large language models, Transformer models, and vector search. Designed for developers who need flexibility and control, Haystack orchestrates state-of-the-art components into pipelines that solve real-world NLP challenges—from retrieval-augmented generation (RAG) to document search and conversational agents.
The framework provides a vendor-neutral approach, letting you integrate models from OpenAI, Cohere, Hugging Face, or your own local deployments. Switch between Azure, Bedrock, SageMaker, or self-hosted infrastructure without rewriting your application. Haystack's explicit component design makes it transparent how data flows through your pipeline, simplifying debugging and optimization.
Haystack includes everything needed for production deployments: database connectors, file conversion, text preprocessing, model training, evaluation, and inference. Scale to millions of documents with production-grade retrievers, customize behavior with your own components, and leverage user feedback loops for continuous improvement. Deploy pipelines as REST APIs using Hayhooks, or develop visually with deepset Studio.
When teams consider Haystack, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Enterprise Knowledge Base RAG
Search across millions of internal documents with context-aware answers combining vector retrieval and LLM generation, deployed on-premises for data security
Multi-Source Customer Support
Resolve complex queries by orchestrating searches across documentation, tickets, and knowledge bases with decision-making logic and provider-agnostic model selection
Semantic Document Discovery
Enable meaning-based search across legal, medical, or research archives using custom embedding models and production-scale vector databases
Conversational Agent with Feedback Loop
Build chatbots that improve over time by collecting user feedback, benchmarking responses, and fine-tuning models on domain-specific data
Haystack supports OpenAI, Cohere, Hugging Face models, Azure OpenAI, AWS Bedrock, AWS SageMaker, and custom local or self-hosted models. The framework is designed to be vendor-agnostic, making it easy to switch providers.
Yes, Hayhooks provides a simple way to wrap pipelines with custom logic and expose them via HTTP endpoints, including OpenAI-compatible chat completion endpoints compatible with interfaces like open-webui.
Haystack provides connectors for multiple vector databases and includes retrievers that scale to millions of documents. You can choose the vector database that fits your infrastructure and switch between them as needed.
Yes, deepset Studio provides a visual interface to create, deploy, and test Haystack pipelines. For fully managed solutions, deepset AI Platform offers end-to-end LLM integration using Haystack architecture.
Haystack Enterprise provides expert support from the core team, enterprise-grade templates, deployment guides for cloud and on-premises environments, and best practices for scaling production systems.
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