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Easy4ALL

About the Project

The Easy4ALL project aims to develop a solution based on the no-code paradigm that allows, through natural language, non-programmers to extend CPCIT4ALL applications, such as HR management, utilities management, or portals, creating new functionalities/modules on top of them without the need for programming. Also, users of this software will be allowed to make requests or interact with the software applications provided by the company in an automated and assisted manner.

Acronym

Easy4ALL

Responsible

Evelin Freire Amorim

Status

active

Starting Date

January 1, 2024

Ending Date

January 31, 2026

Effective End Date

Global Budget

Funding

Website

Datasheet

Members

Team Leaders

Evelin Freire Amorim

Assistant Researcher

Team Members

Alípio Jorge

Centre Coordinator

Evelin Freire Amorim

Assistant Researcher

José Nina Andrade

Luís Filipe Henriques

Researcher

Nuno Ricardo Guimarães

Assistant Researcher

Dissemination

INESC TEC has a unique and differentiating management model, improved over its 35 years of history. Reflecting its unique position between academia and industry, the management at INESC TEC carefully balances, in a hybrid model, the academic culture of scientific freedom and dialogue with a culture of efficiency and responsibility in management.

link for

Associated Centres

Artificial Intelligence and Decision Support

Our Laboratory of Artificial Intelligence and Decision Support (LIAAD) conducts research in the fields of Artificial Intelligence, Machine Learning, Data Science, and Modelling. These areas are cross-cutting and apply to all sectors of society and the economy. The vast amounts of data being collected, alongside the ubiquity of digitalisation and sensorisation, are increasingly creating opportunities and challenges for automating decision support. The combination of Machine Learning and complex models is transforming the economy, healthcare, justice, industry, science, public administration, and education. This encourages us to invest in diverse technological and scientific approaches and perspectives. Our overarching strategy is to explore the flow and diversification of data, and to invest in research lines that will lead to the development of applied Artificial Intelligence foundations and models that are responsible and human centred.