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Feature|Videos|September 9, 2026
How ClaimGuardRx's Purpose-Built AI Detects and Counters Diversion Tactics
Author(s)Bryan Dennison, Paysign
Key Takeaways
- Recognize what makes ClaimGuardRx's proprietary, domain-specific LLM different from repurposed fraud tools.
- Understand how the platform's detect-and-respond design shortens the time between spotting a threat and acting on it.
Bryan Dennison breaks down the purpose-built technology behind ClaimGuardRx and how its detect-and-respond design keeps manufacturers ahead of evolving diversion tactics.
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Sponsored by Paysign
Bryan Dennison, Senior Vice President of Sales and Product at Paysign, explains the technical foundation of ClaimGuardRx, a proprietary large language model (LLM) trained specifically on patient affordability claim patterns rather than adapted from a general-purpose model. He covers how the platform's voice-driven interface lets nontechnical users ask plain-language questions and receive analytical insights, supporting data, and recommended next actions in seconds.
Dennison also highlights what he considers the platform's true differentiator: its ability to close the loop by not just detecting maximizer activity, but helping teams design and deploy counter-algorithms in response. He also shares Paysign's product roadmap, from expanding detection coverage to building toward a multimodal, agentic platform.
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