Klevu has been positioned in the inaugural 2024 Gartner® Magic Quadrant™ for Search and Product Discovery

Klevu has been positioned in the inaugural 2024 Gartner® Magic Quadrant™ for Search and Product Discovery

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Machine Learning for Ecommerce
Reach the next level of productivity with machine learning

Automate what you couldn’t before. Our state-of-the-art machine learning models are tailored to your ecommerce KPIs. Klevu AI software is self-taught and can continuously adapt to changes in your customer’s behavior.

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Trusted by the world’s leading brands and retailers

Machine Learning Models
Utilize your data with ML models built for ecommerce growth

Your store generates tons of data. Machine learning can help you use it. Enhance the product discovery experience by automatically combining the right products with the right audience and continuously learning with user behavior analytics.

Utilize your data with ML models built for ecommerce growth

ML-Powered Search & Discovery
Take advantage of machine learning built for ecommerce

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Become data-driven to drive more search-led revenue

Using clickstream, segmentation, and collaborative filtering, Klevu is like a supercomputer powering product discovery for shoppers with the highest intent.

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Combine machine learning with easy-to-use merchandising tools

Machine learning dynamically optimizes category pages, balanced with the control of business rules set in the admin panel.

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Product recommendations that your shoppers will actually like

API and no-code solutions display various strategies and pages that combine AI magic with precision curation.

Klevu AI
How Klevu AI works

Klevu AI encompasses linguistics and continuous machine learning to improve online shopping experiences. Klevu shines in a crowded search & product discovery market because of the comprehensiveness of the AI offering, and how it impacts user experience.

How Klevu AI Works
Klevu employs a mix of vector and non vector databases

Vector Databases
Klevu employs a mix of vector and non-vector databases

As part of automated catalog enrichment, without the need for any store-specific learning, we use word vectors to identify context-sensitive synonyms to add to the product catalog data, color normalization, and AI-driven facet management. We have other databases for everything else so that we can customize the machine-learning models whenever necessary.

Ecommerce ML Models
Customize Klevu machine learning models to your needs

Klevu machine learning models can be customized to suit your needs. You can configure the learning window, whether to add more weight to clicks, conversions, and/or attributes, and various search preferences such as fuzzy score, filtering, and decompounding.

Customize Klevu machine learning models to your needs
Continuous experimentation in the Klevu AI Lab

Klevu AI Lab
Continuous experimentation in the Klevu AI Lab

We have an in-house AI lab that consists of research scientists that continue to experiment with linguistics and machine learning to find the most cutting-edge use cases and technology that we then apply to our existing products. We are constantly innovating new ideas in visual discovery, conversational commerce and predictive analytics.

Machine Learning Features
See how machine learning can help your customers discover your products

Power your search and product recommendations site-wide with easy-to-use controls, automation, and a fully composable front end.

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Predictive Autocomplete

As soon as shoppers start typing, results dynamically change to ensure the most relevant products show. Use an easy-to-use interface to customize your search overlay, or use API to build a fully-custom experience.

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Product Data Enrichment

Without any prior learning, automatically and manually add synonyms, normalize measurements and index that enriched data in real-time, and expand your product data by 2-3x without any manual work.

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Continuous Learning

Clicks, purchases, and product reviews all influence AI within the context of individual storefronts to dynamically optimize results, driving more revenue automatically.

Klevu machine learning matches clickstream and purchase behavior across the Klevu platform, industry-wide, and recommends products trending amongst similar types of shoppers.

Shopper Intent

With Klevu, your users can use search to be able to find answers to common questions, not only product retrieval but content and pages.

Trend Analysis

Klevu machine learning identifies trending products using data from the Klevu platform automatically boosting trending products.

Keyword Intent

Klevu’s intent parsing service deconstructs query inputs and identifies the intent behind, and the topic of the query.

Deep Neural Networks

Klevu uses deep learning techniques to train its models, which helps them to learn as a human would, instead of being trained by a human. Deep learning is proven to be faster and more accurate than other ML models.

Case Study: Topps Tiles
Topps Tiles: The Search for A Discovery Tool


Case Study: Eurokangas
How an omnichannel retailer doubled click through rates online in 2-weeks with Klevu Discovery Suite

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Case Study: Sarah Raven
Dr Barbara Sturm used Klevu AI search and merchandising to achieve 61% click-to-conversion rate

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Case Study: Monrovia
B2B plant retailer Monrovia saw a 50% increase in use of on-site search with Klevu

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Case Study: Laura Mercier and BareMinerals
Personalized Klevu search improves conversion and engagement rates for Bare Minerals and Laura Mercier

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Support Services
Technology that works and people who care

You don’t have to do it alone. Ensure you have a support team by your side that is highly responsive, knowledgeable, and hard-working.

Client Testimonials
Here’s why retailers Heart Icon Klevu

“We’ve found that using Klevu AI increases AOV, on site customer experience, CLV, and ROAS.”

Tim Ryan
Tim Ryan Director of Digital at Seasalt Cornwall

“Now with Klevu, we have time and resources available to focus on scaling the business.”

Rachael Maine
Rachael Maine Digital Product Owner at Avon

“Klevu really works out of the box. We have been impressed by the flexibility of the APIs – straightforward, well documented, stable and working as advertised.”

Jakub Halva
Jakub Halva Head of Operations at Tom & Co

“Klevu has allowed us to bring a feature set to our client that allows their customers to shop more efficiently.”

Andrew Potkewitz
Andrew Potkewitz Group Director at Overdose

Let’s grow together

Take the next step, tell us your goals, and let us exceed them together.