Search that understands people, not just keywords.
Alfinder's AI semantic search understands what your customers mean, even when they use natural language, slang, or incomplete phrases. Typos and synonyms handled automatically.
Stores using AI Search see an average +20% increase in conversion rate.








Why this matters
Understands Natural Language
Customers type the way they think: full sentences, questions, slang. Alfinder understands all of it and maps it to the right products in your catalog, no keyword matching needed.
Typo & Synonym Tolerance
"Wireles headphons" or "Bluetooth earbuds"? Both return the same results. Alfinder handles misspellings, abbreviations, and synonyms so customers always find what they need.
Conversion-Ranked Results
Results aren't just relevant; they're ranked by purchase probability. Products that are most likely to convert appear first, turning more searches into sales.
How AI Search works.
Customer types naturally
A shopper types something like "blue winter jacket under $100" or "comfortable running shoes for daily use", using their own words, not your product titles.
AI parses intent & attributes
Our model extracts the real intent: product category, color, size, price range, and other attributes, even when they're expressed informally or with typos.
Semantic matching finds products
Instead of matching keywords letter-by-letter, Alfinder understands meaning. "Running shoes" matches "athletic sneakers" because the intent is the same.
Results ranked by conversion
Results are ordered by purchase probability, not just relevance score. Products that shoppers with similar queries actually bought appear at the top.
Features in detail
Multi-language queries
Supports English, Arabic, and mixed-language searches. A customer can type in any language or mix languages, and still get accurate results.
Auto-complete & suggestions
As shoppers type, intelligent suggestions appear: popular searches, trending products, and relevant categories that guide them to the right product faster.
Filter-aware search
Queries like "Nike shoes under $80 in size 10" automatically apply filters. No need for the customer to manually set price range, brand, or size; it happens seamlessly.
Zero-result recovery
When an exact match isn't found, Alfinder suggests the closest alternatives instead of showing an empty page, keeping shoppers engaged instead of bouncing.
Real-time index sync
Your product catalog syncs automatically. New products, price changes, and inventory updates are searchable within minutes, with no manual re-indexing needed.
Average conversion lift
Search response time
Query understanding accuracy
Perfect for
Fashion & apparel stores
Shoppers describe outfits in their own words, like "casual summer dress for a beach wedding," and find exactly what they need, even across thousands of SKUs with complex attributes like size, color, material, and occasion.
Electronics & tech stores
Customers use technical terms inconsistently: "wireless earbuds", "Bluetooth headphones", "AirPods alternative". Alfinder maps all variations to the same product category and returns the best matches.
Large catalogs (500+ products)
The bigger your catalog, the harder it is for customers to find what they want with basic search. Alfinder makes large catalogs feel small and navigable, and every product is discoverable.
Frequently asked questions
Most stores are live within 15 minutes. Install the app, and Alfinder automatically indexes your product catalog. No coding or manual configuration required; it works out of the box.
Yes. Alfinder understands Gulf, Egyptian, Levantine, and Saudi Arabic dialects, plus mixed Arabic-English queries. A customer can type in Franco-Arabic or switch between languages mid-query.
No. Alfinder returns results in under 200ms, faster than most native search solutions. The search widget loads asynchronously and doesn't affect your store's page load speed.
Alfinder's zero-result recovery kicks in, suggesting the closest matching products, related categories, or popular alternatives. You also get analytics on zero-result queries so you can fill catalog gaps.