Google Cloud Vision API Product Search vs Ximilar Visual Search

Google Cloud Vision API Product Search lets retailers build catalogs from products and reference images, organize them into product sets, and find visually or semantically similar items from query images. Supported categories include homegoods, apparel, toys, packaged goods, and general. Query images can come from Google Cloud Storage, a web URL, or a base64 string. Optional product-label filters support AND or OR expressions under documented rules. Calls are available through REST, RPC, and Google Cloud client libraries, while CSV import can create product sets, products, and reference images in bulk. The free plan covers prediction and storage for 0–1,000 images monthly. Listed paid storage starts at $0.10 per 1,000 images; prediction is $4.50 or $1.80 per 1,000 at higher tiers. Index updates occur approximately daily. Limits include 20 MB images, 10 MB JSON objects, and 16 images per request.

Ximilar Visual Search uses AI-powered vector search to find visually similar images in a collection. It indexes visual descriptors for fast searches across millions of images and supports metadata filters. Images can be added through the API by URL or Base64 data, with up to 10 records in one request. Search operations include visual search, multi-image queries, similarity ranking, and object detection followed by similarity search. Described uses include reverse image search, finding items by photo, recommendations for similar products or graphics, and matching images in collections. The platform is accessible through an API and web interface and can be integrated with existing systems. For visual search, Ximilar says it creates encoded image representations and discards the image files, though collections may retain customer-provided URLs. The free plan provides one collection of up to 1,000 images. Paid plans start at $69/mo; monthly API credits expire at period end, while separately purchased credit packs do not. Ximilar is based in Brno, Czech Republic.