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Standard search fails anyone who doesn't type the exact keyword. Zipchat's agentic AI search understands intent, searches your entire catalog semantically, and returns the right products every time.
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Zipchat Agentic AI Search works in two places: inside the chat conversation, and as a full replacement for your store's search bar.
When a visitor opens the Zipchat widget and asks "do you have something for sensitive skin under $40?", the AI doesn't check a FAQ list. It searches your entire catalog, product pages, blog posts, and knowledge base semantically, then returns a precise recommendation. The same search intelligence runs across website chat, WhatsApp, Instagram DM, Messenger, and email.
When a customer clicks your store's search bar, Zipchat takes over. A full-screen overlay opens. They type anything — a keyword, a description, a question — and the agentic engine returns up to 12 matched products and up to 6 relevant pages, ranked by intent. No catalog re-tagging, no synonym tables, no manual optimization.
Zipchat reads your catalog, product pages, descriptions, blog posts, and store policies. Setup runs automatically; no restructure or re-tag required.
A customer clicks your search bar or opens the chat widget. Any query goes through the Zipchat agentic search engine first — keyword, natural-language description, image, or voice note.
Zipchat returns the most relevant products and pages based on what the customer meant, not just what they typed. If nothing matches, the AI opens automatically and continues the conversation.
Keyword search requires customers to guess the right words. Agentic search understands what they mean.
| Customer query | Zipchat agentic search | Standard search |
|---|---|---|
| "running shoes under $100 for desert trails" | Matched products by price, use case, and terrain | No results (keyword mismatch) |
| "gift for someone who likes fishing" | Semantic match across catalog | No results |
| "something like CeraVe for dry skin" | Finds alternatives by category and attributes | No results (brand not in catalog) |
| No match found | AI opens, conversation continues, sale is recoverable | Empty page, customer leaves |
| Customer searches in French on an English store | Full cross-language semantic matching | No results or wrong results |
| Customer sends a photo | Visual search, finds similar products | Not supported |
| Customer sends a voice note | Transcribed and searched in real time | Not supported |
| Customer wants a discount | AI can create and apply a discount on the spot | Shows nothing |
A customer can upload a photo and ask "find me something like this in black", or send a voice note describing what they're looking for. The same agentic search engine runs across every channel where Zipchat is deployed.
Standard search shows an empty page. Zipchat starts a conversation. When the overlay returns no results, the AI picks up where search left off: it can answer follow-up questions, suggest alternatives, create a discount to close the sale, or connect the customer to a human agent.
An AI chat panel opens directly inside the search overlay. The customer continues without leaving the search experience.
The full chat widget opens with the customer's query already filled in. The conversation picks up exactly where search left off.
The same agentic engine adapts to any language and any knowledge source. No separate setup, no separate accuracy.
Multilingual
Zipchat's semantic search is locale-aware and multilingual. A customer searching in French on an English-language catalog still receives accurate, relevant results.
The AI replies in their language automatically. No separate localization setup, no per-locale catalog, no diverging accuracy.
For SaaS
For SaaS companies, Zipchat Code runs the same agentic search against your documentation, codebase, API reference, and support history. Customers get a precise, sourced answer in seconds.
Support teams deflect repetitive tickets. Sales teams answer technical pre-sales questions without looping in engineering. Trial users get answers before they churn.
See how Zipchat Code works for SaaS · See what powers Agentic AI Search
Traditional search tools return a list of products and stop there. Zipchat combines agentic search with a full AI conversation layer. When search doesn't find a match, the AI continues the conversation, answers follow-up questions, creates discount codes, checks order status, and guides the customer toward a purchase. No standalone search tool does this.
No. Zipchat reads your existing product pages and catalog data as-is. There are no synonym tables to build, no boosting rules to configure, and no manual tagging required.
It replaces the behavior, not the visual element. Your search bar stays visible. When a customer clicks it, Zipchat intercepts the action and opens a full-screen search overlay instead of the native search results page.
For Shopify stores, product changes trigger a re-index within one hour. All stores also run automatic daily or weekly syncs to keep the catalog current.
The overlay displays a customizable "no results" message and automatically opens the AI chat after two seconds, with the customer's query pre-filled. The AI can suggest alternatives, answer questions, or escalate to a human agent.
Yes. The agentic search engine scales with catalog size. Indexing runs in the background and does not affect the live store experience.
Yes. Customers can search in their own language even if the catalog is written in a different language. Zipchat's semantic engine handles cross-lingual matching automatically, and the AI replies in the customer's language.
Yes. For SaaS companies, the same agentic search engine runs against your documentation, codebase, and support ticket history. Customers and support agents get sourced answers from your actual product knowledge in seconds.
