Artimetro

This is a serverless project for artists and art lovers empowered by custom AI methods.

Technologies used

What are their services?

Our client is from France, they offer a digital web application to the Mexican artist community that works as a social network but also as an application that measures the knowledge and social influence of the artists, based on these parameters a user can gain more influence in the social network. The application is planning to continue expanding to other countries in the future.

Video presentation, using the social network

What we made.

We built the web application presented in this case study, including the AI methods.

• Velo Node.js backend with MVC architecture

• Database development

• User account

• A module that controls user roles & permissions

• Analytics module with Machine Learning and custom AI methods

• Frontend user interface logic

• Quiz component

• UI/UX and custom design

• Admin dashboard

Statistical module, and Machine Learning

How does it work?

The Artimetro system utilizes machine learning for different functionalities:

A user signs up to start using the web application, the first phase presented to the user after sign up is the initial quiz with a total of 7 questions, unless the user answers this quiz topic can not access the tools in the application.

Once the user answer the 7 questions, is requested to fill out the minimum information to become a member through a wizard screen that does not allow the user to continue unless it is filled out.

Then the user is taken to a lobby where the user has certain important pages "Your Space", "Improve your State", "Quiz", and "Personal account" These are social tools that are measured and analyzed by AI methods, users can use "Improve your State" to fill out the information, request to become artist presenting their artwork, signature artist manifest, art love manifest and many more. Between the quiz component, which is empowered by AI methods to evaluate user actions, the user can improve their level of influence on the social network.

If a user is less serious about influencing the artistic world within the social network can simply create a profile, follow artists, view art galleries, and present a social network public profile that others can view and follow (which will always generate influence measured as a concrete value) The importance of the influence level is that would highly affect the art of the rest of artists depending on the user parameters.

Users can sponsor other users based on their knowledge, knowledge is computed with Machine Learning models that evaluate the artistic knowledge of a user.

Sponsor functionality

Once a user receives sponsorship, the platform supports the artist in their reachability to promote and sell their art.

Type of questions using Machine Learning, and convolutional neural networks

User public profile