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
Prediction with Deep Learning
Company:
CREA SP.
Problem:
Quickly identify potential fraud in ARTs.
Objective:
Predictive model for detecting fraud, non-compliance, and ART volume.
Public:
Technology team.
NLP automation (text, video, voice)
Company:
Comgás.
Problem:
Improve and support the process of continuous improvement of the service provided by the company.
Objective:
Artificial intelligence solution to support the customer service team in continuous improvement and quality standards.
Public:
Operations team.
Edge computing system
Company:
SAUÁ.
Problem:
Create a solution to support wildlife monitoring.
Objective:
Affordable GPS telemetry solution for intelligent wildlife monitoring.
Public:
Operations team.
Predictive maintenance
Company:
Itubombas.
Problem:
Prevent downtime due to equipment failure and service interruptions.
Objective:
Artificial intelligence for predicting failures in the company's motor pump operations.
Public:
Product team.
Structure and governance for data analysis
Company:
CESB.
Problem:
Improve the strategic vision of the business.
Objective:
Development of a solution for sanitizing, organizing, and visualizing data on the management of soybean production areas.
Public:
Product team.
Distributed systems
Company:
BCG.
Problem:
Meet the demand for online ticket purchasing services.
Objective:
Develop a new architecture based on microservices, containers (Docker), orchestration with Kubernetes, and cloud computing.
Public:
Technology team.
Natural language with generative AI
Company:
Curadobia.
Problem:
Optimize customer service.
Objective:
Automated customer service agent with a human touch: fashion recommendations, tips, and curation.
Public:
Operations and IT team.
Predictive Model
Company:
Atvos.
Problem:
Predict freight rates and freight services.
Objective:
Predictive model for determining the best price for contracting inbound freight for harvest and off-season.
Public:
Operations team.