Find products from a photo.
A customer sees a product they love: on a friend, in an ad, on the street. They upload the photo. Alfinder finds the closest match in your catalog instantly. No words needed.
Visual search is especially popular with Arabic market shoppers who frequently share inspiration on social media.
Upload an image to search
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Upload an image to search
95%89%84%78%72%65%Why this matters
Snap & Shop
See something you like in real life? Take a photo. Alfinder analyzes the image and finds matching or similar products in your store. It's the most natural way to search: no words needed, no keywords to guess.
Visual Attribute Extraction
Alfinder doesn't just match pixels; it understands what's in the image: product type, color, style, pattern, material, and shape. This deep understanding means accurate matches, not random look-alikes.
Social Media Integration
Your customers save inspiration from Instagram, Pinterest, and TikTok. Image search bridges the gap between "I love this" and "Where can I buy it?", turning social inspiration into direct sales.
How Image Search works.
Upload a photo
Customers tap the camera icon in the search bar and choose to take a new photo, upload from gallery, or paste an image from their clipboard. Screenshots from Instagram or TikTok work perfectly.
AI analyzes the image
Our vision model extracts visual attributes: product type, dominant colors, style cues, patterns, and material textures. It can identify a specific type of bag, shoe, or piece of furniture from a complex scene.
Visual similarity matching
Alfinder compares the extracted visual features against every product in your catalog. It scores products by visual similarity and returns the closest matches, even if the exact product isn't in stock.
Ranked visual results
Results appear ranked by visual similarity score. Customers see exact matches first, then similar alternatives, giving them options even when the exact product isn't available in your catalog.
Features in detail
Multi-object detection
Upload a photo of an entire outfit, and Alfinder identifies each item separately (jacket, shirt, pants, shoes) and finds matches for each one. One photo, multiple product discoveries.
Screenshot-friendly
Customers save product screenshots from social media all the time. Alfinder processes these images even with UI overlays, watermarks, or partial views, extracting the product from the noise.
Color-accurate matching
Color is critical in visual search, especially for fashion and home decor. Alfinder's vision model accurately distinguishes between subtle shade differences (navy vs royal blue, cream vs white).
Works with any image source
Camera photos, gallery uploads, screenshots, copied images, drag-and-drop: any way a customer gets an image to your search bar works. Supports all common formats: JPEG, PNG, WebP, and HEIC.
Image analysis time
Visual match accuracy
Avg. higher engagement rate
Perfect for
Fashion & apparel
A customer sees a dress on Instagram and screenshots it. They upload the screenshot to your store's search and instantly find the same dress, or similar styles in different colors, prices, and sizes. This turns social media browsing into direct sales.
Home decor & furniture
Customers photograph furniture they see in showrooms, hotels, or friends' homes. Image search finds similar items in your catalog, matching style, color, and design aesthetics for a cohesive look.
Any visual product category
Jewelry, accessories, shoes, bags, art prints, phone cases: any category where visual appeal drives purchasing decisions. Image search captures the "I want exactly that" intent that text search can't express.
Frequently asked questions
Standard smartphone photos work perfectly. The image doesn't need to be professional quality; screenshots, casual photos, and even slightly blurry images are handled well. The product just needs to be reasonably visible in the frame.
Yes. If a customer uploads a full outfit photo, Alfinder can identify and separate individual items: the jacket, the bag, the shoes. It focuses on the most prominent product and offers results for each detected item.
Image search works best with visual product categories: fashion, furniture, accessories, home decor, electronics. For products where visual appearance is less distinctive (like supplements or books), text search is usually more effective.