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Solo Developer Builds Graph-Powered Agentic Fraud Investigation System at Hackathon

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Developer Rohan Kumar, competing solo under team name BROTHERHOOD at Hacker House Goa '26, built an AI-driven fraud investigation agent as part of a TigerGraph challenge. The system uses TigerGraph's graph database to map relational connections between transactions, devices, cards, customers, and billing regions, treating fraud detection as an investigation workflow rather than a simple classification problem. Unlike conventional fraud models that flag individual suspicious transactions, the agent traverses connected evidence across the network, assesses uncertainty, and retrieves historical case context before recommending a next-best action. A policy engine sits between the evidence layer and the final decision, ensuring recommendations are grounded in structured data rather than LLM guesswork. The project includes a live dashboard, a public GitHub repository, and a demo video, with the core design principle being that the graph finds the evidence, the policy decides what to do with it, and the agent connects the two.

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