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Implementing cutting-edge solutions using Artificial Intelligence

Recommendation engine

Use a recommendation engine trained on data from your business to increase your sales.

Leverage Machine Learning and Deep Learning techniques to build a recommendation engine tailored for your needs, trained with your user's purchase and usage history and your products or contents.


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Use cases

E-commerce

Suggest to your users the items they are most likely to buy

E-learning

Show only relevant content, articles and courses to your students

Social

Friend suggestions and curated social feed

News feed

Show the most relevant news to each user. Create a personalized experience

Fintech

Investment portfolio recommendations

Real Estate

Display only relevant properties for your potential buyers

How are they built?

Learn more about how things are done behind the scenes

Trained on your data

No one knows your customers better that you so we use your data to train your own recommendation engine in order to improve performance

Machine Leanring

Using Machine Learning and Deep Learning techniques to build the best engine for you. We start by doing data exploration and then find and tune the best model possible.

Production deployment

Deploy the solution to your own servers, no matter where they are hosted. You don't need to be tied to a new pay-per-use service that bills you every month.

Flexible & Scalable

Trained models are portable and easy to scale, let us take care of the training so you can focus on getting the most out of the predictions




What can they do for me?


With a recommendation engine you can get:


  • Item recommendations to a user: Same way as Netflix recommends you movies and series or Amazon products
  • User recommendation to an item: Know wich customers are more likely to buy each product so you can better target your marketing efforts
  • Item recommendation to items: Offer other relevant products that users are likely to buy when selecting a specific product


For your business and customers this means:


  • Peronsalized user experience Show only relevant content and products
  • → Cross-sell/ Up-sell: Offer relevant products based on customer preferences
  • → Increased customer loyalty: User are more likely to return to you if you offer them a personalized experience
  • → Increased LTV: Improve customer's LTV by improving the basket size and retention

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