Let Shoppers Search in Their Own Words

01 What is AI product search?

It is store search that matches what a shopper means, not only the words they type. Each product is stored with a description of its meaning, so a search finds the right products even when the shopper uses different words from your titles. Stock, price and your rules then set the order.

02 How is it different from keyword search?

Keyword search finds products whose titles contain the words typed, so a different word finds nothing. AI search compares meanings, so "warm jacket for hiking" finds insulated outdoor coats. The best setups use both: exact matches for product codes and brands, meaning for everything else.

03 Does it work with Shopify?

Yes. On Shopify we connect search to your catalogue and stock through the store's own data, and keep the index up to date as products change. It can sit beside your current search, so you can compare results before you switch over.

04 Does it work with WooCommerce?

Yes. On WooCommerce we index your products by meaning and serve results to your store's search box and search page, with stock and price from your store. The same approach works for a custom store built on your own database.

05 Can it recommend products too?

Yes. From the same index we show similar items and items often bought together, on product pages and in the cart. Recommendations come only from your catalogue and your stock, and your rules can pin or hide products.

06 Can shoppers search in other languages, or by voice?

Yes. Gyanee.ai, a shopping assistant we built, takes questions by text or voice in 9 languages, including Hindi and Hinglish. A store can do the same, so a shopper finds products listed in English while searching the way they talk.

07 Do we have to replace our current search?

No. We can add search by meaning beside the engine you run today, such as Algolia, and use it where keyword search fails. At TrueWholesale, synonym-aware Algolia search resolves trade names, common names and warehouse descriptions to the same product.

08 How do you know the new search is better?

We test it on real searches from your store, each with the products a shopper should find, before launch and after every change. After launch we watch the searches that find nothing, which show where the catalogue or the search needs work.

09 Is our data kept private?

Search needs your catalogue, not your shoppers' personal details. With hosted models from OpenAI or Anthropic, what is sent is processed by that provider. With open models on your own servers or cloud through Ollama, it stays inside your network.

10 How much does AI product search cost?

Three things drive the cost: the size of your catalogue, the store platform, and whether you want recommendations as well as search. Tell us about your store, and within two working days we come back with an approach, a rough timeline and a rough number.

11 How long does it take to build?

It depends on the catalogue and the platform. We start with the searches that fail most often today, so shoppers feel the change early. We agree the timeline at the discovery call.

12 Who owns the code and the search index?

You do. The code goes into your own code repository, and the cloud account and the index are in your company's name. Our team joins as collaborators, and you can remove our access at any time.

13 What happens after launch?

We monitor search after launch, keep it updated and improve it as new models arrive. As your catalogue grows, we add new synonyms and test searches, so results stay right for new products.