TruthSys AI
Decision intelligence for fraud systems
Truthsys is building decision intelligence for fraud and risk teams. Today, banks and payment platforms rely on AI assisted fraud decisions but often lack visibility into why decisions were made, how reliable they are, or how to generate evidence for audits and compliance. Truthsys provides decision level visibility, stability analysis, and audit ready evidence to help teams evaluate, validate, and improve fraud decisions. By helping institutions prove and improve high stakes decisions, Truthsys reduces costly false positives and builds greater trust in AI driven fraud systems.
Deonna Owens is the founder of Truthsys and a master’s student in Computer Science at Stanford University. She is a published AI researcher whose work spans AI fairness, reliability, and evaluation systems, including first-author research on responsible AI and multi-LLM frameworks. She previously worked at Adobe Research, where she led projects on AI evaluation and bias mitigation, and as a software engineer at Amazon, Cisco, and Boeing. Deonna also won Best Paper in Stanford’s flagship natural language processing course for her research on fairness methods in language models.
