AI Search is now generally available

Cloudflare’s AI Search combines Workers AI, Vectorize, R2, and Browser Run into a fully managed index and retrieval pipeline. Since we launched AI Search over a year ago, we’ve seen developers use it to power a wide range of search use cases, from searching internal documentation to powering search for their websites. We use AI Search ourselves to power search on our own blog and developer docs.

Starting today, AI Search is generally available. And as part of it, we've expanded and improved our support for multimodal formats beyond text, adding native image embeddings, optical character recognition (OCR) for PDFs, and support for larger files.

As part of general availability, we’ll start billing for AI Search on November 1, 2026, and continue to offer a generous free tier on all Workers plans.

An image is more than the sentence used to describe it. Product texture, screenshot state, chart relationships, document layout, and fine visual detail can all disappear when pixels are compressed into a caption.

AI Search now preserves both signals: it embeds image pixels directly for visual retrieval while retaining captions for textual understanding. To keep these richer representations efficient, AI Search leverages Matryoshka Representation Learning (MRL), allowing smaller embeddings to retain useful information while keeping storage manageable and search fast.

Although we originally supported retrieval over images, the implementation was naive: we would perform object detection, generate a caption, and then embed that text. This made images searchable, but only through the details captured in the caption. Now, we do both — caption-based understanding and native image retrieval.

Native multimodal retrieval is available today with the Qwen3-VL-Embedding model. At query time, AI Search checks whether your instance’s embedding model supports images. If it does, a query image is embedded directly by that model, landing in the same vector space as your indexed images and text.