How to create a personalized experience for every user

Alie is an AI-powered recommender as a service for businesses that want to create a personalized user experience for their customers. Alie’s AI is powered by algorithms that are designed to anticipate your customer's needs in real-time and create personalized experiences.

Alie ingests item data, user data & behavioral data from your website or app to provide real-time recommendations. Implementing Alie for your website/app is fairly easy and can be achieved in four simple steps.

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Learn how simple it is to set up recommendations for your website/app!


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Trusted by global leaders

Uni Cards
Thanti One
Expo Dubai
Simply South

Frequently asked questions

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Yes. We are committed to improving our product and customer experience. We maintain a priority list of new features & UI upgrades based on customer requests. Our team is quite strong in research, innovations, and faster implementations. You can check our latest list of features here.

By default, content-based models are tuned to reduce the cold start issues. Alie uses the End-User Interaction algorithm where Alie starts showing similar item recommendations even if there are very few (or just one) user-item interactions.

Yes. Definitely. 

Alie uses browser cookies to capture user activity & product data to generate relevant recommendations, for guest or anonymous users!

Our pricing is purely usage-based or pay-as-go - you will never have to pay more than you use. We have flat pricing of $ 0.0005 per API request, whereas the minimum monthly charge would be $99. Please check our pricing page for more details.

Muvi's core features include built-in CDN for content delivery, DRM for content protection, multiple monetization models, an online video player, and automatic encoding and transcoding. Muvi offers 100+ features designed to deliver a seamless streaming experience. Sign-up for our Free Trial Now!

We use collaborative filtering (matrix factorization, nearest k, supervised learning …) algorithms, which work on the interactions (views, purchases…), and content-based algorithms, which work on the item metadata (titles, descriptions…). You can get more info here