Argus is a highly configurable dual-use anomaly detection analytical AI Agent that continuously analyzes the open-source web, in multiple languages, to predict anomalous and nefarious behavior hidden in plain sight.
Argus reads, understands, and learns at scale as it scours everything from news and social media to company filings and microprocessor manuals to predict supply chain influence, software vulnerabilities, logistics resilience, viral mis/disinformation, insider threats, and more.
Foreign adversaries are manipulating and hampering the U.S. supply chain, creating potential shortages in areas like semiconductors and other key hardware. This interference has a direct impact on many DoD operations.
Most data in the world is public, with many foreign threats hiding in plain sight. And given the sheer volume of that data, it is difficult for decision-makers and defense analysts to locate those threats to protect the U.S. supply chain. To make matters worse, traditional analytics and static AI tools don’t work because they aren’t smart enough and can’t scale.
Argus and its continually learning AI detect anomalies in the U.S. supply chain that are hidden in public data. This enables it to identify vulnerabilities and emerging threats quickly.
So far, Argus has analyzed over 50 million documents relating to more than 6 million entities and more than 12,000 investment projects in more than 180 countries. Through its analysis, Argus has already inferred over 59 million relationships, resulting in the discovery of valuable insights that directly help locate active foreign threats and secure the U.S. supply chain.
To do what Argus is doing with traditional methods would cost the DoD an estimated $238 million, or the equivalent of 2,000 analysts, per year.
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