The Problem: When Data Loses Its Meaning In most companies today, the real issue isn’t a lack of data—it’s that the data is trapped in meaningless lakes. We’ve spent years worrying about formats and schemas (structural interoperability), but we’ve completely ignored what the data actually represents.  This gap is a dealbreaker for anyone trying to build reliable AI agents. Without…