https://repositorio.ufu.br/handle/123456789/5154 2026-08-24T21:07:31Z 2026-08-24T21:07:31Z https://repositorio.ufu.br/handle/123456789/49802 2026-08-24T18:49:39Z 2026-07-30T00:00:00Z

Title: Inteligência artificial como interface de gestão: um modelo de micro-ERP aplicado ao varejo digital Abstract: The objective of this technical-technological report was to develop and evaluate a cloud integration architecture, driven by artificial intelligence agents, for the automation of data flow and inventory management in a digital retail microenterprise. As the problem situation, it was identified that the manual synchronization of inventory across multiple sales channels generated a high risk of stockouts, order cancellations, and loss of real cost control due to the absence of automated calculations. The developed solution consisted of creating an invisible micro-ERP, structured on a cloud-based relational database, integrated through communication interfaces, and operated entirely by a conversational interface within a messaging application via artificial intelligence. As for the results achieved, there was a reduction in synchronization time from hours to a few seconds, the mitigation of the risk of sales without physical stock, and the recovery of financial control through the automatic application of the First-In, First-Out (FIFO) accounting rule, in addition to increased data security through the use of cryptography and access restriction.

2026-07-30T00:00:00Z https://repositorio.ufu.br/handle/123456789/49794 2026-08-24T17:45:10Z 2026-08-05T00:00:00Z

Title: Modelo integrado de capacitação em Inteligência Artificial e automação: um relato técnico-tecnológico em uma corporação de tecnologia e telecomunicações Abstract: The objective of this technical-technological report was to describe the implementation process of an integrated training model in Artificial Intelligence and automation within a technology and telecommunications corporation, to support digital transformation and process optimization. As a problem situation, a knowledge asymmetry was identified between the organization's innovation hub and the operational areas, marked by a lack of digital literacy in automation and Artificial Intelligence, keeping teams tied to manual and repetitive tasks, with loss of efficiency and hidden costs. As a solution, the internal innovation team structured an integrated training and technological acceleration model, aiming to form citizen developers. Highlighted achieved results include direct service to the fourteen mapped business areas and, according to participation records consolidated by the innovation team, without duplication across programs, approximately 3,000 employees who participated in at least one training initiative, of which 1,200 professionals advanced to continuous technical follow-up modules, becoming qualified to use approved tools. Additionally, nine of the ten pitches were approved by the sponsoring directorates, promoting the safe decentralization of innovation and redirecting team efforts previously dedicated to strictly bureaucratic routines toward activities of greater analytical value.

2026-08-05T00:00:00Z https://repositorio.ufu.br/handle/123456789/49771 2026-08-24T16:01:06Z 2026-07-22T00:00:00Z

Title: Estratégias de internacionalização e escolha dos modos de entrada: estudo de caso de uma startup brasileira

2026-07-22T00:00:00Z https://repositorio.ufu.br/handle/123456789/49764 2026-08-24T15:39:47Z 2026-07-30T00:00:00Z

Title: Business Intelligence para indicadores de produtividade em um centro de distribuição logística Abstract: The objective of this technological report was to describe the development and implementation of a Business Intelligence (BI) solution to support productivity management in a logistics distribution center located in Uberlândia-MG. The identified problem situation consisted of the use of manually populated spreadsheets based on daily data extractions, making the operational process susceptible to rework, delays in updating information, and analytical limitations. As the adopted intervention, Azure Databricks resources, VBA scripts, and dashboards developed in Power BI were utilized, aiming to automate data processing and expand the capacity for visualizing managerial information. As achieved results, greater agility in data processing and availability was observed, along with the creation of previously nonexistent indicators and analytical views, providing enhanced support for the managerial decision-making process.

2026-07-30T00:00:00Z