People are often overwhelmed by too much information and too many choices. 

All companies wanting to ensure customers enjoy a wonderful experience on their site, have to help them in finding the right option they are looking for. Recommendation systems enable companies to provide this kind of support to their customers. 

Recommendation service is AI based, usually working as a black box. 

Veos Digital Recommendation system is cognitive support, and not only automated support: like all services supplied by Veos Digital it is suitable for all those companies and decision-makers that want to gain both insight and control to work with the AI, rather than waiting for it to produce unexplainable results.

Characteristics

It is adaptive

Its architecture evolves autonomously on your catalogue in real-time, during training phase

Solved issue: cold start.

It is knowledge-based

Suggestions are based both on users’ history and users’ habits. This allows a flexible clusterization of users.

Solved issues: new user“grey sheep”.

It combines traditional algorithms with a multilayer approach

Provided suggestions are based both on general and specific similarity in characteristics (text, images, technical specifications)

Solved issues: over-specialization, limited content analysis

Additional features for Decision Makers and Analysts

  • Automatic organization of products in new subcategories, making the catalogue more accessible and modular.
  • Insights visually on the diversity of your catalogue.
  • Insights on which products generate the highest revenues and why.
  • Automatic highlight of products that better suit your business globally, depending on current trends

Scientific Base

  • Convolutional Conditional Variational Auto-encoder
  • NLP
  • Hypergraph Variational Autoencoder
Recommendation AI Architecture

Integration

Our system is RESTful APIs based. It’s a standard adopted by many Software producers to provide applications to Third Parties.

Simple integration

Zero maintenance

Pay per use