Prototypes delivered
Our Call for Projects is the way we let the market know which projects are available for the next semester. During this period we receive applications for initiatives from companies, NGOs and government institutions with their business challenges.
Contributing to society is a fundamental pillar of our model. That's why we make available the prototypes developed by our students over the years.
Our project-based learning model develops computer skills, business skills and socio-emotional skills through solutions to real market problems.
We hope that other companies, non-governmental organizations (NGOs) or government entities will find here a comprehensive repository of innovative and alternative solutions to meet their challenges.
The prototypes can be freely downloaded, customized and adapted to meet similar problems, and we believe that these prototypes have the potential to be widely used throughout the technology community, promoting collaboration and innovation on a large scale.
Project
Company
Course
Optimization and operational research
Company:
Klabin.
Problem:
The need to obtain methods for restricting resources during the process of cutting and producing raw materials.
Objective:
Developing an optimization solution for the TRIM machine for cutting paper reels, meeting the demands of different customer orders.
Public:
Klabin's internal employees.
Prediction with Deep Learning
Company:
Aegea.
Problem:
Identification of fraud patterns.
Objective:
Determine whether a consumer behavior is likely to be fraudulent or not.
Public:
Technology team.
Predictive Model
Company:
Unipar.
Problem:
Evaluation of employee health data.
Objective:
Create a solution with a predictive model to support the evaluation of employee health data.
Public:
Technology team.
Predictive Model
Company:
Rede Gazeta.
Problem:
Advertising revenue prediction strategy by economic sector.
Objective:
Develop a predictive model of advertising revenues by economic sector.
Public:
Technology team.
Predictive Model
Company:
Compass.
Problem:
Identification of fraud patterns.
Objective:
Model for detecting anomalies in consumption and identifying fraud patterns.
Public:
Technology team.
Predictive Model
Company:
CVM.
Problem:
There is no risk prediction model for FIDC-type funds.
Objective:
Predicting the risk of the FIDC fund, assessing the likelihood of a problem occurring, whether due to future insufficiency or lack of provision.
Public:
CVM's internal data analytics team.
Predictive Model
Company:
Mobly.
Problem:
Improve the purchasing provisioning process and stock control of SKUs.
Objective:
A model capable of generating a sales forecast and purchase suggestion with quantity for each sku.
Public:
Mobly's internal data analytics team.
Predictive Model
Company:
Bettha.
Problem:
There is no prediction model to suggest the best job or training for the candidate.
Objective:
Recommending the best vacancy or training for the candidate user of the platform.
Public:
Bettha's internal data analytics team.