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I’ve been thinking a lot about why conversations around OSINT feel increasingly shallow, even though the tools we use have never been more powerful. We have more data, automation, dashboards and AI-generated summaries than at any point in the history of intelligence. And yet, when I look at how conclusions are drawn, how confidence is expressed, and how often assumptions go unchallenged, I can’t escape a deeply uncomfortable feeling: We are collecting more than ever and thin

You think you know Amsterdam? You don’t. Even if you’re born and raised there. For OSINT investigators, analysts, and journalists, searching only for “Amsterdam” means missing half the signal. The city hides behind slang, symbols, codes, and multilingual aliases. This post shows how language masks location, why alias awareness matters, and how Boolean and regex uncover Amsterdam’s hidden digital footprint across the open web, social media, and the dark web.

OSINT isn’t about collecting public data, AI already does that better than humans. OSINT is about pressure-testing reality. In digital investigations, organisational security, and business risk, OSINT turns fragmented public signals into defensible understanding. As AI increases visibility but not judgment, OSINT remains a human discipline: questioning sources, timelines, intent, and absence. This article breaks down what OSINT really is, how it’s used, why businesses rely on