Pay less taxes using web agents, a directed graph, and Dijkstra's algorithm (berke.bearblog.dev)

A new tool called TreatyHopper has been introduced to automate the process of optimizing profit repatriation for multinational corporations, startups, and tax advisors. By modeling the complexities of international tax law as a directed graph and employing Dijkstra's algorithm, the tool identifies the most cost-effective routes for transferring profits across jurisdictions while minimizing tax liabilities. This innovation promises significant savings—potentially in the billions—by reducing the labor-intensive and often imprecise manual research traditionally done by tax professionals. TreatyHopper utilizes AI-driven web agents to compile comprehensive data on Double Taxation Agreements (DTAs) between countries, allowing it to generate an edge list representing the relationships and tax rates between various jurisdictions. This algorithm transforms the maximization of profit retention into a minimization problem, thus enabling efficient route optimization. Future developments may incorporate Graph Neural Networks to assess risks associated with various paths, enhancing the tool’s capability to navigate complex tax landscapes. This advancement marks a significant step forward in tax-planning technology, providing transparency and efficiency in international financial operations.