PrestaShop Artificial Intelligence

AI Semantic Search — PrestaShop

The search that understands intent, not just keywords

At a glance
  • Semantic search by AI embeddings: your customers find by meaning, not by exact keyword match
  • Instant autocomplete wired to your theme's search bar, with no jQuery dependency
  • Works with OpenAI, Mistral AI (EU/GDPR hosting) or any OpenAI-compatible API
  • Compatible with PrestaShop 8 and 9, multistore and multilingual
  • Batch + cron indexing, query cache, hybrid semantic + keyword mode
PrestaShop 8 & 9 Multistore Multilingual GDPR-ready
  • 30-day refund
  • 12 months updates
  • 24h support
www.datafirefly.com/en/
AI semantic search returning relevant products in PrestaShop
v1.0.0 · updated 2026-07-15
What it does

The short version.

01

Search by meaning

Vector embeddings capture the customer's real intent. “Gift for a newborn baby” surfaces the right products even if none contain those exact words.

02

No more “no results”

Classic search fails on synonyms, typos and natural phrasing. Semantic search stays relevant where the SQL LIKE gives up.

03

Smart hybrid mode

Combines semantic similarity with keyword matching on the product name: the best of both worlds, so you never miss an obvious exact match.

04

Autocomplete that converts

A visual suggestions menu (image, name, price) attaches to the theme's search bar and guides the customer to the product in a few keystrokes.

The long version

Everything you'd want to know before you install.

A detailed look at how AI Semantic Search — PrestaShop works, why we built it the way we did, and the thinking behind the features above.

§ 01

Internal search is the most overlooked conversion lever

A visitor who uses the search bar has strong purchase intent. Yet PrestaShop's native search relies on keyword matching: it fails as soon as the customer uses a synonym, makes a typo or describes what they want in their own words. Every “no results” is a lost sale and a customer who leaves for a competitor.

§ 02

How semantic search works

The module turns each product — name, brand, categories, features, description — into a numerical vector (embedding) using an AI model. At search time, the customer's query is converted into a vector the same way, then compared against the whole catalog by cosine similarity. The result: products are ranked by closeness of meaning, not by literal presence of words. “Shoes for running in the rain” surfaces your waterproof running shoes, even if that exact phrase appears nowhere.

§ 03

Hybrid mode: meaning without ever missing the obvious

Purely semantic search can sometimes under-rank an exact product-name match. Hybrid mode fixes this by boosting products whose name contains the query keywords. You get the relevance of AI plus the reliability of classic search, combined in a single ranking.

§ 04

Control your costs and your privacy

Choose your embedding provider: OpenAI, Mistral AI for European GDPR-compliant hosting, or any OpenAI-compatible gateway. The query cache avoids re-billing repeated searches, and checksum-based re-indexing ensures a price or stock update triggers no unnecessary API call. You keep full control of the model, the dimensions and the budget.

§ 05

Built for production

Batch indexing with a progress bar, scheduled indexing via a secured cron, automatic cleanup of disabled products, query logging to understand what your customers search for. Multistore and multilingual compatible, without Composer or jQuery, following PrestaShop 8 and 9 conventions.