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New updates and improvements at Cloudflare.

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Vectorize
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  1. Return up to 50 query results with values or metadata

    Vectorize

    You can now set topK up to 50 when a Vectorize query returns values or full metadata. This raises the previous limit of 20 for queries that use returnValues: true or returnMetadata: "all".

    Use the higher limit when you need more matches in a single query response without dropping values or metadata. Refer to the Vectorize API reference for query options and current topK limits.

  1. Vectorize indexes now support up to 10 million vectors

    Vectorize

    You can now store up to 10 million vectors in a single Vectorize index, doubling the previous limit of 5 million vectors. This enables larger-scale semantic search, recommendation systems, and retrieval-augmented generation (RAG) applications without splitting data across multiple indexes.

    Vectorize continues to support indexes with up to 1,536 dimensions per vector at 32-bit precision. Refer to the Vectorize limits documentation for complete details.

  1. List all vectors in a Vectorize index with the new list-vectors operation

    Vectorize

    You can now list all vector identifiers in a Vectorize index using the new list-vectors operation. This enables bulk operations, auditing, and data migration workflows through paginated requests that maintain snapshot consistency.

    The operation is available via Wrangler CLI and REST API. Refer to the list-vectors best practices guide for detailed usage guidance.

  1. Create fully-managed RAG pipelines for your AI applications with AutoRAG

    AI Search Vectorize

    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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