App Details

Scorecard

 

Our take: Revery AI is a great option for online fashion retailers who want to provide a more engaging and personalized shopping experience for their customers. You would want to try it out as it gives an immersive experience to your customers. 

Pros and Cons

Pros

Cons

Introduction of Revery AI


Online shopping has become a popular and convenient way to buy clothes, especially during the pandemic. However, one of the biggest challenges that online fashion retailers face is how to provide a satisfying and realistic try-on experience for their customers. Without being able to touch, feel, and see how the clothes fit on their bodies, many customers end up buying the wrong size, color, or style, leading to high return rates and low customer satisfaction.

Revery AI is a startup that aims to solve this problem by creating a virtual dressing room solution that leverages computer vision and artificial intelligence. Revery AI helps online fashion retailers create a more engaging and personalized shopping experience for their customers, where they can mix and match any outfit and visualize it on a model that looks like them.

An Overview of Revery AI

Revery AI was founded in 2020 by Kedan Li, a former Google engineer who has a Ph.D. in computer vision from Carnegie Mellon University. The company is backed by Y Combinator, one of the most prestigious startup accelerators in the world. Revery AI has already integrated with the largest fashion retailer in Southeast Asia and is partnering with some of the world’s largest fashion brands.

Revery AI’s technology is based on state-of-the-art deep learning models that can generate realistic images of clothing items and human models in various poses and backgrounds. The technology can also handle complex scenarios such as layering, occlusion, deformation, and transparency. Revery AI’s virtual dressing room can be easily embedded into any e-commerce website using a simple code snippet or accessed through an API.

Features of Revery AI

Revery AI offers several features that make it stand out from other virtual dressing room solutions:

User experience

Revery AI’s user interface is simple and intuitive. Users can access the virtual dressing room by clicking on a button or scanning a QR code on the retailer’s website. They can then select a model that resembles them or customize their own model using sliders and buttons. They can also upload a photo of themselves to get a more accurate match.

Once they have chosen a model, they can start browsing through the clothing items by category or brand. They can drag and drop items onto their model or click on them to see how they look. They can also use filters to narrow down their choices by color, size, fit, style, etc.

Users can switch between different views of their model such as front, side, back, etc. They can also zoom in, rotate, and move their model around to see the details of the clothes from different angles.

Users can save their outfits by clicking on a heart icon or add them to their cart by clicking on a shopping bag icon. They can also share their outfits with their friends on social media platforms by clicking on a share icon.

Pricing

Revery AI offers just 2 pricing plans for its virtual dressing room solution:

Final Verdict

Revery AI is an innovative and affordable solution that helps online fashion retailers create a virtual dressing room experience for their customers. It enables customers to try on clothes virtually using realistic models that look like them. It also helps retailers increase online engagement and conversion while reducing return rates.

Revery AI is easy to integrate with any e-commerce platform using a simple code snippet or API. It also offers a free plan for small and medium-sized businesses that have up to 10, 000 monthly active users.

Revery AI is a great option for online fashion retailers who want to provide a more engaging and personalized shopping experience for their customers.

 

Leave a Reply

Your email address will not be published. Required fields are marked *