Agentic AI, a new paradigm in which AI systems not only respond to commands, but also make autonomous decisions, work with other agents and act proactively, is a turning point in automation. This session will explore how these agents can transform various sectors and functions. It is essential to understand how this new generation of AI will impact business and society in general.

Presenter:

• Lali Soler, Digital Area Director, Eurecat

Participate:

• Rafael Giménez, Data & AI Lead, Quantion

• Martí Norbeto, CEO, Timbal AI

• Ray G. Butler, Director of Data Science, Butler Scientifics

Eurecat.org | LinkedIn

Director of the Digital Area at Eurecat, with extensive experience in Artificial Intelligence and Big Data, she specializes in developing cutting-edge digital solutions for various industries. Soler’s role combines digital technologies with business strategy to deliver impactful results. She is passionate about fostering innovation and empowering teams to achieve excellence in technology-driven projects. She is responsible for the center’s digital technology strategy, its results, and research activities.

www.quantion.com | LinkedIn

Rafael Giménez is the Data & AI Lead at Quantion, a Barcelona-based technologyconsultancy that works to develop innovative and robust solutions for corporate
environments. Always at the cutting edge of technology, at Quantion Rafael is responsible for defining the AI strategy and driving the team’s activity in Data,
Machine Learning and Generative AI projects. Before working at Quantion, Rafael has led Data and Artificial Intelligence teams in large companies, research centres
and even a Fintech start-up.

Agentic AI is the technology of the moment, but its large-scale adoption still needs to overcome several key barriers to generate sustained impact. The AI Team at Quantion develops agent-based solutions that incorporate robustness as a key pillar from design and that ensure that responses are observable, evaluable and aligned
with legal and strategic frameworks. In the talk, we will explain our Agentic AI multiagent architecture, secure and scalable, and present our success stories deployed in production and built from a focus on reliability, collaboration and autonomy.

www.timbal.ai | LinkedIN

Since early on, I’ve been passionate about turning ideas into real ventures – building purpose-driven teams and sustainable businesses. With a background in computer engineering and a growth mindset, I started in a SaaS startup, where I led an intrapreneurship initiative. This sparked my entrepreneurial journey, founding Neway BCN and Fixed Company. After selling Neway to the market leader, I began investing in tech-driven ventures. Today, I channel that experience into building Timbal AI, that helps enterprises integrate AI into their core operations. Our mission: empower companies to unlock the full potential of autonomous, secure, and useful AI.

2024/25 was the year of AI hype, countless pilots, bold promises, and the feeling that anything was possible. But most projects never made it to production. In 2026, a new phase begins: companies no longer want to play with AI, they want to own it, strategically, safely, and with control. If AI will do most of the work, understanding how it operates is key to staying competitive. At Timbal AI, we’ve built an open framework that enables companies to develop autonomous systems under their own control. In this session, we’ll share how we move from hype to real impact, and what the future holds.

www.butlerscientifics.com | LinkedIN
Bluesky | ResearchGate

Ray G. Butler earned his degree in Computer Science from the University of Las Palmas de Gran Canaria and holds an Executive MBA from EADA, Barcelona. He began his professional career at companies such as Abengoa, Giesecke & Devrient, and Panlab. In 2012, he founded Butler Scientifics, where he led the development of AutoDiscovery, a data exploration software designed to help research teams at hospitals, universities, and pharmaceutical companies better understand diseases through large volumes of clinical data. Currently, with a strategic focus on the automation of data science, he collaborates with leading medical centers and pharmaceutical multinationals, and combines this work with teaching in the degree program in Applied Sciences and Technologies for Sport at UPC (EUNCET).

As part of the BioConverse project, Butler Scientifics has distilled over 10 years of experience in biomedical data exploration to develop a tool based on large language models (LLMs), specifically designed to guide researchers and clinical professionals with no technical background through these processes. Unlike traditional assistants focused on answering isolated questions, BioConverse functions as a true digital mentor—structuring analytical workflows, suggesting statistical strategies, warning against conceptuals errors, and facilitating the interpretation of results. This presentation will share preliminary findings on the impact of this approach on the efficiency and autonomy of novice users in real-world biomedical settings.