FindAstra helps your WooCommerce store understand what shoppers actually mean, not just the exact words they type. Someone searching for “comfortable shoes for hiking” will find your “Trail Running Sneakers” even when the title never mentions comfort or hiking.
Ordinary keyword search only matches products that literally contain the words a shopper types. So a customer who describes things in their own way lands on a “no results” page and leaves. FindAstra closes that gap. It reads the intent behind each search, puts the most relevant products first, and offers helpful suggestions instead of dead ends.
And the free version runs completely on its own. There are no API keys to paste, no account to create, and no monthly fees. The AI runs right inside the shopper’s browser, so nothing about your catalog or your customers is sent to an outside server, and you can index your entire catalog with no product limit.
When you click index, FindAstra reads each product and builds a small understanding of what it is. When a shopper searches, it compares their wording to that understanding and lists the closest products first. The first time it runs, the browser downloads a small AI model (about 33 MB) and reuses it from then on, so searches stay fast.
A separate paid version is available at findastra.com for stores that want more. It adds optional server-side engines for very large catalogs (using your own OpenAI or Hugging Face key), multilingual search for WPML and Polylang, and built-in search analytics. The free version here is complete on its own, and nothing in it is locked or time limited.
Which external service (if any) FindAstra contacts depends on the search engine you choose during setup. Each is described below, including what data is sent and when.
Used by the default Local engine. The first time the Local engine runs (when you index products in wp-admin, or when a shopper performs a search), the browser downloads a roughly 33 MB open-source AI model from the Hugging Face model hub and caches it locally for later visits. Only the model files are fetched. No store, product, shopper, or site data is ever sent. After the download, all search runs entirely in the browser.
Hugging Face terms of service: https://huggingface.co/terms-of-service . Privacy policy: https://huggingface.co/privacy
Used only if you select the OpenAI engine and enter your own API key. At index time, the text of each product (its title and the fields you choose to include) is sent to OpenAI to generate an embedding; at search time, the shopper’s query text is sent. Requests are authenticated with the API key you provide and are made only while the OpenAI engine is the active provider.
OpenAI terms of use: https://openai.com/policies/terms-of-use . Privacy policy: https://openai.com/policies/privacy-policy
Used only if you select the Hugging Face engine and enter your own access token. The same data as the OpenAI engine (product text at index time, query text at search time) is sent to the Hugging Face Inference API to generate embeddings, authenticated with the token you provide, and only while the Hugging Face engine is the active provider.
Hugging Face terms of service: https://huggingface.co/terms-of-service . Privacy policy: https://huggingface.co/privacy