How BlueArc’s AI Graph Knows Which Businesses to Trust

Risk systems have long specialized at evaluating individual users—people have physical attributes, devices, addresses, and other identifiers that make it possible to build coherent identity graphs. But businesses are a different story. They don’t have a single form; they exist as collections of domains, websites, employees, customer relationships, press coverage, and more. This complexity has made them harder to assess—until now.

At BlueArc.ai, we’ve developed a Business Risk Knowledge Graph to bring structure to this mess. By applying AI and large language models to publicly available information, we help risk and Trust & Safety teams understand how businesses are connected, who they really are, and whether they can be trusted.

Here are four ways we differentiate good from bad businesses:

• Legitimate SMBs: We verify small businesses by mapping their relationships with known entities—investors, press mentions, physical locations, and founders with reputations.
  
  
• Multi-Domain Enterprises: Large companies often operate many different domains. We help confirm when lesser-known domains are part of a trustworthy parent company.
  
  
• Scam “Islands”: Fraudulent websites may look good, but often have no external footprint. We identify these isolated sites and highlight them as high-risk.
  
  
• Fraud Clusters: Scammers often launch many similar sites as they scale. Our graph links them through subtle clues—shared infrastructure, writing patterns, or metadata.

By surfacing the hidden connections between businesses, BlueArc brings clarity to one of the hardest problems in risk: figuring out which businesses are legitimate and which are not. Our partners—leading tech platforms and financial institutions—use these insights to make faster, smarter decisions powered by AI.

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