Stop optimizing for devices and start optimizing for experiences.

Sentient Aware is an AI-powered recommendation engine that increase AOV and conversions on your site. Through Aware’s computer vision and deep-learning capabilities, the AI makes the most accurate and relevant recommendations to your shoppers.

Intelligent Recommendations

Unlike traditional product recommendation solutions, Aware does not rely on collaborative filters or metadata to make highly relevant suggestions to your shoppers. Instead, Aware uses computer vision to see the product your shopper is interested in and looks in your catalog to see which products are the most similar.

Personalized Shopping, Evolved

With Aware’s AI recommendation API, you can extend your recommendation capabilities to create a “personal shopper” experience on your site. This experience enables your shoppers to have a visual conversation with the AI to find the exact products they are looking for. Just like if they were interacting with a store associate, Aware can understand a shopper’s intent just by looking at the images the shopper interacted with.

Living Pages

With Aware’s living pages, when shoppers interact with email or ad images, the AI can make product recommendations on the landing page that are highly relevant to their interests or the offer in the campaign.



Aware uses Sentient’s artificial intelligence platform to understand your products and how they relate to each other in hundreds of visual and data dimensions.

Aware’s online learning capabilities understand your shopper’s intent based on their real-time and/or historical activity.

It combines its understanding of the products and your shoppers to deliver new, better-performing customer experiences—better product selection, better navigation, and better recommendations—across all of your key digital touchpoints.


What is visual search technology?

Visual search technology comes in many varieties but all approaches center on the fact that it’s easier to find what you want looking at a product than typing out a description of it. At Sentient, our Aware platform analyzes the images themselves on hundreds of vectors, understanding what the product is and, importantly, what other products are similar to the user’s search intent.

When is visual search useful?

Visual search is ideal for products we buy largely based on their appearance–think clothes and apparel and home decor, for example. Products that are more utilitarian don’t work nearly as well. After all, you’d never buy a nail or a screw based on how it looked; you’d buy it based on its size and if it’ll get the job done. Visual search gives users a more intuitive way to find products, more like browsing a store that evolves to their taste then interacting with a spreadsheet.

How is personalization done in ecommerce?

Traditionally, ecommerce personalization hasn’t been all that personal. Brands have used things like emails with first names or cohort recommendation–think “users like you also purchased”–as personalization strategies. Aware is different. It uses each click of each individual user to surface products that fit that user’s sense of style. It doesn’t use historical data or groups of similar uses: it analyzes unique shoppers, in-the-moment. It’s true personalization.

What is a product recommendation engine?

A product recommendation engine helps customers easily find the products they’re looking for. Some engines are based on the products a user has viewed, purchased, or otherwise interacted with in the past. Other software products such as Sentient Aware assist shoppers find what they’re looking for in-the-moment instead. This helps ensure that customers always find the products they are specifically looking for each time they visit your website and not products they may no longer be interested in.

How do you build a product recommendation engine?

Most recommendation engines require you to keep track of every customer click and action, then group them into myriad cohorts, sort of like a vast collection of venn diagrams. And even then, you’re relying on historical data that relies on old patterns that may no longer be valid. Aware saves brands from both those chores. It doesn’t need tons of outdated, historical data because it’s driven by its understanding of data-rich product images.


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