| Today’s modern retail and e-commerce companies produce huge amounts of visual content – product photos, promotional videos, user-generated clips, audio voiceovers, influencer reels, etc.
When teams look for files using visual similarity, spoken content, or contextual semantics, old-style search tools fall short because they rely on manual tags or simple keyword indexing, which fail to understand the meaning of this content. Instead of just scanning filenames or descriptions, semantic and multimodal search systems turn text, images, video, and audio into a shared semantic space that enables retrieval based on meaning rather than exact metadata matches. |
