[vc_section][vc_row css=”.vc_custom_1681910300131{padding-bottom: 30px !important;}”][vc_column]
<\/div><\/div>[\/vc_column][\/vc_row][vc_row full_width=”stretch_row” bg_type=”bg_color” css=”.vc_custom_1681913912294{padding-top: 30px !important;padding-bottom: 30px !important;}” bg_color_value=”#ededed”][vc_column][vc_row_inner][vc_column_inner][vc_column_text]<\/p>\n
[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space]
EURECAT<\/a> | Linkedin<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] [\/vc_column_text][vc_column_text][\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space] Opsphere<\/strong><\/a>\u00a0| LinkedIn<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] Jos\u00e9 Julian Ariza is a Cloud Architect and DevSecOps specialist with more than 20 years of international experience leading technology transformation initiatives across multiple industries. His expertise includes cloud architecture, platform engineering, applied artificial intelligence, observability, and large-scale automation. Alongside his professional work, he actively participates in technical training and knowledge sharing, helping organizations adopt AI in a practical, secure, and business-oriented way. He have worked on global high-availability platforms, large-scale e-commerce systems, and production environments where AI is already part of daily operations.<\/p>\n<\/div>\n<\/div>\n [\/vc_column_text][vc_empty_space] <\/div><\/div>[vc_empty_space][vc_column_text][\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” bg_type=”bg_color” css=”.vc_custom_1683718841357{padding-top: 30px !important;padding-bottom: 30px !important;}” bg_color_value=”#ffffff”][vc_column][vc_row_inner][vc_column_inner width=”1\/4″][vc_empty_space][vc_single_image image=”71945″ img_size=”full”][vc_empty_space][vc_column_text]<\/p>\n AVENTEC<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] Andreu Gim\u00e9nez is an AI Engineer and Data Engineer at Aventec SL, where he develops AI models and data architectures applied to the urban water cycle. He holds a BSc in Computer Engineering and an MSc in Data Science from UPC (FIB), and served as a teaching assistant for the CBI4AI course at ESADE, in collaboration with CERN.<\/p>\n<\/div>\n<\/div>\n [\/vc_column_text][vc_empty_space] <\/div><\/div>[vc_empty_space][vc_column_text][\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” bg_type=”bg_color” css=”.vc_custom_1683718841357{padding-top: 30px !important;padding-bottom: 30px !important;}” bg_color_value=”#ffffff”][vc_column][vc_row_inner][vc_column_inner width=”1\/4″][vc_empty_space][vc_single_image image=”71949″ img_size=”full”][vc_empty_space][vc_column_text]<\/p>\n Gestmusic<\/a><\/strong> | KAI Stories<\/a><\/strong> | LinkedIn<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] Miquel Garcia is a Post-Production Manager in the audiovisual industry, working at Banijay Iberia through Gestmusic. He specializes in overseeing post-production processes and drives innovation in the production of audiovisual formats. His work focuses on integrating new technologies and optimizing workflows, with the aim of exploring new ways of producing that support and enhance creativity. In a dynamic media environment, he collaborates closely with creative and production teams to deliver high-quality content for diverse audiences.<\/p>\n<\/div>\n<\/div>\n [\/vc_column_text][vc_empty_space] <\/div><\/div>[vc_empty_space][vc_column_text][\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” bg_type=”bg_color” css=”.vc_custom_1683718841357{padding-top: 30px !important;padding-bottom: 30px !important;}” bg_color_value=”#ffffff”][vc_column][vc_row_inner][vc_column_inner width=”1\/4″][vc_empty_space][vc_single_image image=”71952″ img_size=”full”][vc_empty_space][vc_column_text]<\/p>\n HP<\/strong><\/a>\u00a0| LinkedIn<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] PhD in Industrial Engineering, with a Master\u2019s in Automation and Robotics and more than 11 years of experience at HP, evolving from Firmware Developer to Firmware Architect. Strong background in firmware, industrial systems, automation, and robotics, with previous research experience at CSIC. Currently focused on architecture leadership and actively promoting data and AI adoption to improve engineering efficiency, scalability, and innovation.<\/p>\n<\/div>\n<\/div>\n [\/vc_column_text][vc_empty_space] <\/div><\/div>[vc_empty_space][vc_column_text][\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][\/vc_section]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":" The potential of Agentic AI in real-world environments through four use cases.<\/p>\n","protected":false},"author":11,"featured_media":71577,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[653],"tags":[],"class_list":["post-72173","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-22-octubre-en-1","category-653","description-off"],"yoast_head":"\nGEMMA BATLLE<\/h2><\/div>
Startup Ecosystem Manager, Eurecat<\/h4>\n
Speakers:<\/h2><\/div>
JOS\u00c9 JULI\u00c1N ARIZA VALDERRAMA<\/h2><\/div>
CEO, Opsphere<\/h4>\n
Beyond Copilots: How AI Agents, the Model Context Protocol (MCP), and AI Governance Are Transforming Cloud Operations, Observability, and Digital Platforms at Global Scale<\/h4><\/div>
From AI Agents and MCP to Observability, Governance and Real-World Operations.
\nMost discussions about AI focus on code generation. However, some of the most valuable applications are emerging elsewhere: technology operations. This session explores real-world examples of how AI is helping operate global e-commerce platforms, improve observability, accelerate incident response, and connect systems through the Model Context Protocol (MCP). We will also discuss governance, cost control, context quality, and practical strategies for adopting AI sustainably in complex enterprise environments. Attendees will gain actionable insights that can be applied immediately to software delivery, cloud operations, and engineering teams.<\/h4>\nANDREU GIM\u00c9NEZ LARRED<\/h2><\/div>
AI and Data Engineer, AVENTEC<\/h4>\n
AI applied to drinking water quality management: prediction of chlorine decay in the Vic network.<\/h4><\/div>
Ensuring water quality requires a global view of the behavior of the distribution network. This view is only possible by combining hydraulic simulation of the network with Artificial Intelligence models capable of interpreting the results. Our project aims to develop models that determine the optimal dosage of chlorine in chlorination stations, so that all points in the network remain within the quality limits established by the regulations.<\/h4>\n
MIQUEL GARCIA HERRERO<\/h2><\/div>
Post-Production Manager, Gestmusic<\/h4>\n
When AI Works as a Team: Agents, Multi-Agent Systems, and Audiovisual Storytelling with KAI<\/h4><\/div>
This session presents KAI, an AI-powered audiovisual storytelling platform that combines multimodal analysis, Large Language Models (LLMs), and multi-agent architectures to transform large volumes of audiovisual content into structured, searchable, and editable stories. Through a real-world television production use case, we will demonstrate how different AI agents collaborate to analyze content, generate metadata, identify narrative elements, and assist editorial decision-making, while integrating directly into professional post-production workflows.<\/h4>\n
\u00c1LVARO L\u00d3PEZ ANTEQUERA<\/h2><\/div>
R&D firmware developer, HP<\/h4>\n
From NLP Models to an Operational AI System for Automated Bug Triage<\/h4><\/div>
Large Format Printing firmware development produces high volumes of complex issues across multiple products and specialized teams, making manual triage inefficient and error-prone. This work presents an AI-driven system that automates bug triage using natural language processing and machine learning. The solution processes Jira data, predicts the responsible team, assigns issues automatically, and analyzes attachments to detect missing information and duplicates. An SVM-based stacking approach achieved the best performance, reaching 77% accuracy. Integrated at scale, the system reduces manual effort and cuts resolution time by over 30%, demonstrating how applied AI can deliver measurable impact in industrial software engineering environments.<\/h4>\n