Yes. Each board in the catalog carries a volume in litres, a length, a width, and a rider weight range as product meta. The bot reads these on every request and matches against the rider's weight and intended water type. The result is two or three in-stock boards with the right volume for the rider, with a short note on why each one fits, rather than a generic sizing chart link.

Yes. Fin box type sits in a product attribute per board, US fin box, slide in, FCS Fusion, or a proprietary fitting. The bot reads the fin box per board and joins on fin SKUs in stock. A shopper asking about a 9 inch centre fin for a Red Paddle Ride 10 8 gets the FCS Connect 9 inch from your catalog, not an invented fin that does not fit the box.

Yes. Board category is a WooCommerce attribute and the bot reads it on every request. A touring query returns long, narrow boards with strong glide. An all around query returns versatile mid range boards. A yoga query returns wider, more stable boards with a soft deck pad. The recommendations track the category rather than guessing from the product title.

Yes. Construction type is stored per board and the bot reads it. A shopper asking about transport on a small car gets pointed to inflatable models with a pump and travel bag. A shopper who races and parks at a fixed lake club gets hard board options with a higher glide rating. The bot also notes the warranty differences between the two construction types.

Yes, if your booking system exposes available slots through the WordPress REST API or a custom endpoint. The bot reads the available Sunday demo windows, the demo fleet contents, and the demo fee credit rule. The actual booking is completed on your booking page, so payment and rider details stay inside your existing flow.

Warranty terms per brand sit in an OpenAI Files vector store. A shopper asking about the Red Paddle Co inflatable warranty gets the Red specific terms; a Fanatic question gets the Fanatic terms. The bot quotes the relevant paragraph rather than pasting a generic warranty page at every shopper with a brand specific question.

Conversation logs stay inside your WordPress database. The data path is browser to WordPress to your OpenAI or Anthropic key directly, with no Sleek server in between. For shops that maintain customer paddling profiles to inform demo and rental fits, those profiles sit in WordPress custom tables you control, separate from the chat logs.

Generic chatbots run on a vendor server and read your help center, not your WooCommerce volume, length, or fin box fields. They cannot recommend a board by volume because they cannot see the volume figure on your product. SleekAI runs inside WordPress, reads the same product meta WooCommerce reads, and runs on your own AI provider key, so the bot answers with grounded, specific recommendations rather than generic SUP advice.