Your customers describe what they want. Now your store understands.
Standard store search only matches exact keywords. Queryra goes further — it understands the full intent behind queries, including price filters ("under $50"), brand exclusions ("not from BrandX"), and sorting preferences ("best rated"). So shoppers find exactly what they want, in their own words.
Default Search vs Queryra
See the difference when a customer searches your store
Default Store Search
Customer searches: "present for my girlfriend"
- 0 results found
- No product has "girlfriend" in title
- Customer leaves → lost sale
- Doesn't understand intent
Queryra AI Search
Same search: "present for my girlfriend"
- Gift Box Set — perfect match
- Skincare Set — great for gifting
- Jewelry Collection — romantic choice
- Customer finds product → sale!
See Queryra in action on real stores
Why Queryra?
Intent-aware search — goes beyond vector similarity to understand what customers actually mean
Custom AI Training
AI learns from YOUR content - articles, products, categories. Not a generic model used by everyone.
Easy Integration
One-click plugin for WordPress & Shopify. Auto-sync on publish. REST API for custom setups.
No External Keys
Everything included. No ChatGPT account. No OpenAI key. Just one Queryra API key.
Lightning Fast
Search results in milliseconds, not seconds. Your users won't wait.
14 days free · No credit card required
How Queryra Works
Most AI search plugins stop at vector similarity — they match the meaning of a query against your products. That's layer one. Queryra adds layer two.
Semantic Vector Retrieval
AI converts your products and search queries into vector embeddings — mathematical representations of meaning. "Gift for dad" finds garden tools, BBQ sets, and watches because the AI understands intent, not just keywords.
This is what every AI search plugin does. It's a good start — but it's not enough.
Intent-Aware Query Parsing
Before searching, Queryra extracts structured information from every query:
- ✓Price constraints — "under $50", "$20–30 range", "cheap"
- ✓Brand preferences — "Nike" (include) or "not from BrandX" (exclude)
- ✓Attribute filters — "red", "wireless", "organic", "size M"
- ✓Sorting signals — "best rated", "newest", "cheapest"
- ✓Exclusions — "not running shoes", "without sulfates"
The result: a customer who searches "wireless headphones under $80, not Beats" gets exactly that — not a generic list of all headphones.
Integrations
Available now and coming soon