Use AI to [improve] the customer experience and drive retail growth

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The challenge

There are many types of consumers. There are the list checkers, the bargain hunters, and the impulse buyers. But one thing they all have in common these days is that, sometimes, the multitude of product options can be overwhelming. This leads to frustrated consumers and lost sales for retailers.

At a glance

Egen Retail Recommendation Engine uses AI to make shopping easier than ever.

With the Retail Recommendation Engine, consumers can instantly find what they want by simply snapping a photo, speaking or typing in a desired item, or recording a video. The Retail Recommendation Engine uses multi-modal search and cutting-edge technology, such as the Google Gemini artificial intelligence model, to help consumers find their desired products through a simplified concierge-assisted journey that eliminates frustrating searches. 

How does it work?
Imagine that you see a photo of a delicious cheesecake you would like to bake. You can add the image to the Retail Recommendation Engine that will generate a shopping list for each of the cheesecake ingredients automatically. 

The Retail Recommendation Engine is not limited to grocery, and can be adapted for shopping experiences from clothing and jewelry to office supplies, home decor, sporting goods, and beyond. The possibilities are endless.

The impact

Offer a smooth shopping experience from anywhere to increase customer satisfaction and drive more purchases.

Delight customers

Give consumers a seamless experience that saves time and eliminates frustration. They can instantly find what they want using multi-modal search that supports text, audio, images, and video, making it effortless to find the right product.

Drive more sales

Increase customer satisfaction and purchases by guiding consumers to their desired products through a simplified concierge-assisted journey that eliminates friction points and frustrating searches.

Boost customer loyalty

Turn one-time buyers into loyal customers by giving them a personal shopping assistant that unearths forgotten favorites and serves up trending products.

Retail recommedation

Insights and resources

Meet the team

Vishwa Vangari
Vishwa Teja Vangari
Principal Software Engineer

Are you ready to [create] new possibilities?

Contact our team today to get started.  

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