LLMModels & ArchitectureUpdated 2026.04.28

Multimodal Search

Also known as멀티모달 검색이미지·음성 검색Visual Search

In one line

Multimodal search lets users query with images, audio or video alongside text — the new entry channel created by 'snap a photo and ask' user behaviour.

Going deeper

Multimodal search lets users query with photos, voice clips or video instead of (or alongside) text. Google Lens, Circle to Search, ChatGPT's image attachments and Perplexity's image upload are the canonical examples. Snapping a shelf, an ad screenshot or a receipt and asking 'what is this?' is now an everyday flow.

For brands, this means visual assets become an entry point in their own right. Packaging, logos and storefront photos have to be identifiable by AI, and the information served after identification — official page, pricing, where-to-buy — has to be clean and easy to surface.

Implementations vary widely by surface. Some read words off the image, others lean on object detection plus a knowledge graph. There is no single playbook; the practical move is to test the major surfaces and see how your brand gets identified and cited per platform.

Related terms

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