From this article. A major announcement just dropped this week, BigID and Atlan are joining forces to create the first catalog unifying structured and unstructured data. The goal is crystal clear, providing a single governance and security foundation that is actually ready for AI. Until now, many companies were flying blind. Business lines are pushing hard to deploy innovative AI workflows, but governance teams lack visibility into the mountains of unstructured, and often sensitive, data feeding these models. By integrating risk signals directly into the catalog, business context is finally linked to security in real time. The Verdict: If your data catalog does not speak the language of both the CDO (Governance) and the CISO (Security) simultaneously, your AI agents will remain prototypes blocked by risk. Managing structured data in a silo is no longer enough. Generative AI feeds on unstructured chaos, and that is exactly where the battle for scale is won. Let’s Discuss: 1. The Blind Spot: Do you have a clear map of the unstructured data feeding your AI initiatives today, or are you just crossing your fingers that nothing sensitive leaks? 2. The CDO and CISO Duo: In your organization, do data governance and cybersecurity share the same operational view, or are they still fighting through support tickets?

Hey folks, for those on the technical side struggling with using LLMs - we've just open-sourced the solution we have been using internally to detect hallucinations (we work with highly regulated industries and can't afford having mistakes in data). You can find a short description & the link here: https://www.linkedin.com/posts/angelina-lesnikova_parseltongue-activity-7439674705277526017-86wL Just heard at the Paperless Lab Academy that AWS is developing a similar neurosymbolic architecture to launch it for their top-tier customers in the upcoming months - you can fork it from our GitHub repository and start using right now ;) Enjoy and please send me your feedback.

Hi folks, I'm Angelina, a founder at sci2sci. I have been concerned with massive amounts of data that remain unused in life sciences organizations because of poor data management practices since my PhD. A few years ago I founded a company and we developed VectorCat - software for automating data governance at scale. We've already governed 100M+ data objects in top biotech and pharma companies, turning them into AI-ready data in a fully compliant way. Happy to connect with data governance professionals: https://www.linkedin.com/in/angelina-lesnikova/. More info about what we do at sci2sci: https://www.sci2sci.com/