haystack
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
💡 Why It Matters
Haystack addresses the need for engineers to create production-ready LLM applications by providing an open-source AI orchestration framework. It is particularly beneficial for ML/AI teams looking to design modular pipelines and agent workflows with precise control over retrieval, routing, memory, and generation. With a solid maturity level, Haystack is suitable for scalable agents, RAG, and multimodal applications, making it a reliable choice for production use. However, it may not be the best fit for teams seeking a lightweight solution or those without the resources to manage a self-hosted option.
🎯 When to Use
Haystack is a strong choice when teams require a comprehensive framework for building context-engineered applications that leverage large language models. Teams should consider alternatives if they need a simpler tool or lack the infrastructure to support a self-hosted solution.
👥 Team Fit & Use Cases
This tool is primarily used by ML engineers, data scientists, and AI developers who focus on building sophisticated AI applications. It typically fits into products and systems involving semantic search, conversational interfaces, and large-scale information retrieval.
🎭 Best For
🏷️ Topics & Ecosystem
📊 Activity
Latest commit: 2026-02-13. Over the past 96 days, this repository gained 857 stars (+3.7% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.