A custom-built Magento 2 / Adobe Commerce extension that lets shoppers upload or snap a photo and find visually similar products using AI image embeddings and pattern matching. Built, installed, and supported by ECOSIRE on your store. One-time license from $499.00 USD for Magento 2 / Adobe Commerce (build-to-order) — includes 12 months of updates and support.

A custom-built Magento 2 / Adobe Commerce extension that lets shoppers upload or snap a photo and find visually similar products using AI image embeddings and pattern matching. Built, installed, and supported by ECOSIRE on your store.
Aucun paiement maintenant. Ceci envoie une demande de devis à notre équipe — nous vous recontacterons par e-mail avec les tarifs et les prochaines étapes.
AI Image / Visual Search turns a photo into a query. Instead of guessing keywords, your shoppers upload an image — or snap one on mobile — and the extension returns the closest matching products from your catalog, ranked by visual similarity. It is purpose-built for fashion, furniture, and lifestyle merchants where look, shape, color, and pattern drive discovery far more than SKU text.
Image upload search returning catalog products ranked by visual similarity score
AI visual embeddings (vector representations) generated per product image for fast nearest-neighbor matching
Pattern and shape recognition that matches texture, silhouette, and color regardless of keyword text
Auto product tagging from visual cues to enrich layered navigation and faceting
Camera and mobile capture support so shoppers can snap a photo and search on the spot
Configurable similarity threshold in admin to tune result strictness (precision vs. recall)
This is not an instant Adobe Commerce Marketplace download. It is a build-to-order extension: ECOSIRE builds the module against your Magento version, theme, and catalog structure, then installs and configures it on your environment. Technically it ships as a proper module under app/code/Ecosire/VisualSearch, wired with di.xml dependency injection, a custom service contract (ImageSearchInterface) so your storefront, REST, and GraphQL layers all call one stable API, and an admin ACL resource so only authorized roles touch configuration.
Under the hood, product images are converted to AI visual embeddings (vectors) during a backgrounded cron-driven indexing job, with an observer on catalog_product_save_after keeping the index fresh as the catalog changes. Pattern recognition and auto product tagging from visual cues enrich faceting. At query time, an uploaded image is embedded and matched against the index; a configurable similarity threshold controls how strict results are. A plugin/interceptor injects the visual-search entry point into your existing search and PDP without core edits.
Works on both Magento Open Source and Adobe Commerce (we adapt to Commerce-only features like Live Search where it makes sense). You get a clean upgrade path, documented config, and ECOSIRE support after go-live.
Sells visually-driven products where shoppers struggle to name a print, cut, or color. Wants 'find me something that looks like this' so customers discover lookalikes and reduce zero-result searches.
Has large catalogs where style and form matter more than SKU text. Needs shoppers to upload an inspiration photo and surface matching sofas, lamps, or rugs by shape and pattern.
Runs a broad catalog where keyword search underperforms on aesthetic intent. Wants AI visual search plus auto-tagging to improve discovery and on-site conversion without rebuilding their search stack.
Achetez la licence sur ecosire.com et téléchargez le module ZIP AI Image / Visual Search depuis le tableau de bord de votre compte.
Extrayez le ZIP dans votre dossier de modules complémentaires personnalisés Odoo sur le serveur (ou téléchargez-le via Applications > Installer à partir du fichier sur Odoo.sh / runbot).
Activez le mode développeur, ouvrez les applications, cliquez sur Mettre à jour la liste des applications, recherchez AI Image / Visual Search et appuyez sur Installer.
Ouvrez le nouveau menu, collez votre clé de licence ECOSIRE, connectez toutes les informations d'identification externes (Shopify, Amazon, Stripe, etc.) et enregistrez.
Exécutez le test de connexion intégré, synchronisez vos 10 premiers enregistrements et planifiez le cron récurrent. Contactez le support si quelque chose échoue.
| Critère | ÉCOSIRE | Construction personnalisée | Concurrent | Odoo natif |
|---|---|---|---|---|
| Photo-upload visual search with similarity ranking | ||||
| AI visual embeddings + pattern/shape recognition | ||||
| Auto product tagging from visual cues | ||||
| Mobile camera capture support | ||||
| Built, installed & supported on your exact Magento/theme | ||||
| REST + GraphQL service contract for headless/PWA | ||||
| Configurable similarity threshold tuned to your catalog | ||||
| Instant self-serve download, no build wait |
Because this is build-to-order, ECOSIRE builds the module against your exact Magento version, theme, and catalog before installing. Typical delivery is roughly 2 to 4 weeks depending on catalog size, embedding model choice, and integration depth (standard Luma/theme vs. headless PWA via GraphQL). We confirm a firm timeline after a short scoping call, install on staging first, then promote to production.
Every build includes a post-launch support window for bug fixes and compatibility with Magento minor releases. Because the module is isolated under app/code/Ecosire/VisualSearch with no core edits, Magento patches and most upgrades apply cleanly. ECOSIRE offers continued support and feature work after the initial window; we keep the service contract and admin config stable so updates don't break your storefront.
Yes. The module is built on standard Magento 2 architecture (service contracts, di.xml, plugins, observers, ACL) so it runs on both Magento Open Source and Adobe Commerce. On Adobe Commerce we can align the visual results with Live Search/Catalog Service where it adds value, but the core visual matching does not depend on Commerce-only features.
We scope this with you. The embedding step can call an external AI provider (vectors only, not raw customer data) or run against a self-hosted model, depending on your data-residency and cost requirements. Product images are embedded during a cron-driven background job; queries embed the uploaded image and match it against your local vector index. We document exactly what is sent where before build.
No. Image embedding runs in a cron-driven background indexing job, not inline with catalog saves. An observer on catalog_product_save_after only flags changed products for re-embedding. At query time the storefront calls the service contract, which performs a fast nearest-neighbor lookup against the prebuilt index, so visual search adds minimal latency to the page.
A custom-built Magento 2 / Adobe Commerce extension that lets shoppers upload or snap a photo and find visually similar products using AI image embeddings and pattern matching. Built, installed, and supported by ECOSIRE on your store.