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Feature

AutoRAG: Fully-managed RAG pipelines for AI applications

AutoRAG is now in open beta, enabling you to build retrieval-augmented generation pipelines without managing infrastructure. Upload your documents to R2, and AutoRAG automatically handles embeddings, indexing, retrieval, and response generation via a simple API or Workers binding.

AutoRAG is now in open beta, making it easy for you to build fully-managed retrieval-augmented generation (RAG) pipelines without managing infrastructure. Just upload your docs to R2, and AutoRAG handles the rest: embeddings, indexing, retrieval, and response generation via API.

With AutoRAG, you can:

  • Customize your pipeline: Choose from Workers AI models, configure chunking strategies, edit system prompts, and more.
  • Instant setup: AutoRAG provisions everything you need from Vectorize, AI gateway, to pipeline logic for you, so you can go from zero to a working RAG pipeline in seconds.
  • Keep your index fresh: AutoRAG continuously syncs your index with your data source to ensure responses stay accurate and up to date.
  • Ask questions: Query your data and receive grounded responses via a Workers binding or API.

Whether you're building internal tools, AI-powered search, or a support assistant, AutoRAG gets you from idea to deployment in minutes.

Get started in the Cloudflare dashboard ↗ or check out the guide for instructions on how to build your RAG pipeline today.

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Source: original entry ↗

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