Media monitoring is the activity of monitoring the output of the print, online and broadcast media to power the decision-making process of people and organizations (e.g., analysis of emerging technologies, competitive intelligence, public reputation, brand awareness). This is a resource intensive task which raises several challenges - The main issue discussed in this talk is how we can process and aggregate a vast amount of multilingual data to discover relevant stories, entities, topics and events; while at the same time meeting the specific information needs of each user. These can range from monitoring specific entities (competitors, brands, influencers), to coarse topics (e.g. “Aerospace Industry”) and even to fine-grained or ephemeral queries (e.g., “Return of the 737 Max model to service”). In this talk we will discuss how we can empower users with relevant and personalized content in the context of the media monitoring setting and introduce the approach Priberam is taking to the problems at hand; in particular by training text retrieval models on-the-fly from user feedback and integrating them in a media monitoring workflow. Sebasti˜ao Miranda is the Head of Development at Priberam, a Portuguese SME that provides cutting-edge Natural Language Understanding and Artificial Intelligence technologies to companies in the Media, Legal and Healthcare industries. He started working on the problem of Multilingual Media Monitoring in 2016 during the 3-year SUMMA European H2020 research project with media partners British Broadcast Corporation (BBC) and Deutsche Welle, further developed during 2019 to tackle the problem of Technology Watch with Brazilian plane manufacturer Embraer. Sebasti˜ao holds an MSc. in Electrical and Computer Engineering from Instituto Superior T´ecnico (University of Lisbon), 2014, and has published work on High Performance Computing, Text Summarization, Entity Recognition and Linking, Crosslingual Clustering, and Fact-Checking.