What they lack is a way to work with it at scale. The data still runs the business, but it can't easily be trusted, reused, or reasoned over consistently by modern software and AI. It runs the core business process of more than 90% of Fortune 500 companies. Yet while the data is reliable by design, its business meaning is often implicit and difficult for AI systems to interpret, which prevents AI from reasoning over it reliably, safely, and at scale. We know why AI systems struggle to interpret enterprise data correctly, that many existing semantic layers stop at technical abstraction, and why business meaning must be made explicit to scale trust, reuse, and automate. We are looking for an expert who understands the heartbeat of SAP—ECC, S/4HANA, and BW—and wants to unlock it for the modern AI world. You will write code that liberates business meaning and context from legacy configurations, ...
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