Case study

Need a smart e-commerce search platform to deliver a dynamic & relevant search experience?

TAE increased AOV by 28% with Zevi's AI-driven search

See how The Ayurveda Experience tailored its online store’s site search to enhance average order value

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Conversion jump


Search CTR


Average order value

Trusted by leading global brands

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Surprise package !! We went ahead and installed Zevi, it did really astonish us when the no. of conversions increased drastically. Plus the founding team was super responsive that helped us move the conversion needle even further.

- Carencure

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The customer service patiently helped me answer the questions and help me adapt the app to the theme. It is definitely recommended!

- Shininglover

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This app has top-notch tech behind it. The app supports multi & mixed search queries. Their search results are very precise and the app comes with an inbuilt ranking model as well. App interface is easy to understand & you can set it up in no time.

- Corvo Styles

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Zevi's app is worth for me to use. Their full features, best customer service and website-friendly are everything I receive when using the app. They also make a google meet call, to fix my website's bug.

- Cocobay Shop

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This app is exactly what i was looking for in a smart search widget for my website. It functions well on my mobile and computer screen. I was not expecting such promt service but he helped me out without wasting any time. Right on the marks! Impressed!

- Dazzles Jewellery

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Good search and filter app. Got some great support from the team as well when we asked them a few doubts. Would def recommend it

- Juicy Chemistry

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seems good app :) ı m gonna use it . Especially search bar seems amazing, its showing products with images.

- Penaccle

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Great App for search based on AI. The results are really accurate with even multiple language inputs. Would recommend it.

- Everything Beautiful

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Why choose Zevi's search over others?



Spell check and typo tolerance
The AI engine provides accurate results regardless of misspellings and errors, and keeps learning from them
Usually based on string distance, which limits its ability to understand and change complex spellings
Synonyms and related keywords
NLP makes use of linguistic associations, eliminating the need for a synonym layer across languages
A synonym layer has to be manually mapped by developers, and needs to be revisited often
Automated suggestions that learn based on user signals
Suggestions are dependent on and limited by existing structured data

Neural search vs String matching

Neural search

String matching

Multilingual and vernacular
Supports different and mixed languages. Ensures that customers can search in their most natural way and still get excellent results
Fails to classify languages. This technology is limited to handling one language at a time, and is very inefficient for languages other than English
Tagging dependency
Contextual understanding greatly reduces dependence on tagging
Heavy reliance on tagging makes it sub-optimal. This process is never-ending, consumes a lot of man-hours and needs to be revisited very frequently