Tag archive
AI shopping agents are starting to browse and buy on behalf of customers. Here's how to make your product catalog readable and searchable by them, with code.
Your store's default keyword search loses sales every day. Here's what an ecommerce search API does, what to look for, and how to add visual and semantic search.
What a reverse image search API actually does, what to look for when picking one, and a side-by-side of the options developers reach for in 2026 (with code).
Fashion shoppers describe what they want in pictures, not words. Visual search closes that gap. Here's what it does, how it works, and how to ship it without an ML team.
Designing Reverse Image Search: The Architecture Behind Google Images Ever wondered how...
Pinterest isn't a search engine. It's a discovery feed that learns what you like from what you click. Here's how to build the same experience for your own app.
Let your Shopify customers search by photo instead of keywords. Sync your product catalog, add visual search to your storefront, and show similar products on every product page.
GPU inference, vector storage, image hosting, backend servers. I broke down every piece of the infrastructure and added up the monthly bill.
Multimodal search lets users search across text, images, and other data types using any of them as the query. Here's how it works, why it matters, and how to build it.
We signed up for Imagga, tested their visual search API, and compared it to Vecstore. Here's how the two approaches differ and when each one makes sense.
Face search lets users upload a photo and find every match across your entire image library. Here's how it works, where it's useful, and how to add it without building your own ML pipeline.
Most reverse image search tutorials involve CLIP models, vector databases, and weeks of setup. Here's how to build one in under 20 minutes with a simple API.