Social networks—whether online platforms like Twitter and LinkedIn, or real-world organizational relationships—contain a wealth of hidden insights. For businesses, investigators, and analysts, understanding how people, entities, and information connect across these networks is vital. But the scale and complexity of these connections are too vast for traditional tools. That’s where artificial intelligence (AI) becomes a
Article - DataMinex
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- May 3, 2025
AI Trends in Investigative Tech 2025
Investigative technology has undergone rapid transformation in the last decade, driven by the explosion of digital data and the evolution of artificial intelligence (AI). In 2025, AI isn’t just supporting investigations—it’s reshaping how they’re conducted. From fraud detection and due diligence to criminal probes and corporate intelligence, AI is enabling faster, deeper, and more scalable
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- May 3, 2025
Detecting Fraud with AI and Open Data
Fraud is no longer confined to forged checks or fake identities. In today’s digital-first economy, fraudsters operate across borders, using sophisticated tactics and creating complex networks. Meanwhile, businesses and governments face increasing pressure to detect and prevent fraud in real time. The good news? Publicly available data and artificial intelligence (AI) are changing the game.
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- May 3, 2025
Ethical AI in Public Data Analysis: Where Do We Draw the Line?
Public data is an incredible asset. From social media posts to company registries and open government databases, businesses now have access to more external intelligence than ever before. Combined with the power of artificial intelligence (AI), this data becomes a tool for market research, competitor analysis, customer insight, and risk detection. But with great power
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- May 3, 2025
Entity Resolution with AI: Challenges & Breakthroughs
In today’s interconnected digital world, organizations deal with massive amounts of data from various sources—customer records, social media, public databases, corporate filings, and more. But all that data is only as useful as it is accurate. Often, the same real-world entity appears under different names, spellings, or formats across systems. This is where entity resolution
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- May 1, 2025
From Public Data to Business Value: Leveraging AI at Scale
In today’s digital ecosystem, public data is everywhere—on websites, social platforms, government registries, and industry databases. But without the right tools and strategy, this abundance becomes overwhelming noise rather than valuable insight. That’s where artificial intelligence (AI) comes in. By automating collection, analysis, and interpretation, AI transforms vast volumes of public data into clear, actionable
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- May 1, 2025
The Future of Investigations: AI-Powered Graph Intelligence
In today’s complex and data-rich world, traditional investigation methods are no longer enough. Whether it’s for law enforcement, due diligence, corporate risk management, or competitive intelligence, modern investigations require the ability to analyze relationships—not just isolated facts. This is where graph intelligence comes in. When enhanced with artificial intelligence, graph-based analysis becomes a powerful tool
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- May 1, 2025
How AI Is Transforming Open-Source Intelligence (OSINT)
Open-Source Intelligence (OSINT) has long been a powerful method for gathering publicly available data to support investigations, competitive analysis, and strategic decision-making. Traditionally, it required significant manual effort—sifting through forums, scraping websites, monitoring news feeds, and verifying sources. But today, Artificial Intelligence (AI) is redefining what’s possible. With automation, pattern recognition, and real-time analysis, AI
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- April 30, 2025
Top Mistakes Companies Make When Using Public Data
Public data offers businesses unprecedented access to market intelligence, consumer behavior, and competitor activity. However, despite its accessibility and potential, many organizations misuse or underutilize it. From legal missteps to flawed analysis, these mistakes can cost companies valuable opportunities—or worse, damage their reputation. Understanding the most common pitfalls in public data usage is essential to
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