DriftGuard started with a simple question: Why do intelligent systems often fail long before conventional metrics indicate anything is wrong? I became fascinated by situations where consensus remains stable while underlying conditions quietly change. Whether in sports betting, financial markets, organizations, AI systems, or risk environments, there often seems to be a gap between the accepted narrative and observable reality. What began as a research project evolved into a working platform designed to help identify blind spots, hidden instability, and emerging divergence before they become obvious. The first version focused heavily on sports, where rapid feedback makes it easier to test ideas. Over time, the framework expanded into other areas including enterprise risk, AI governance, supply chain analysis, and market intelligence. DriftGuard is still in beta, and I'm actively looking for feedback. If you're interested in sports analytics, risk intelligence, anomaly detection, or exploring overlooked signals, I'd love to hear what you think and how you might use it.

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DriftGuard: Elucidate. Extrapolate.

DriftGuard: Elucidate. Extrapolate.