Designing compliant, audit-ready AI systems for complex financial workflows.
This initiative focuses on applying AI to one of the most error-prone and fragmented areas of financial operations: cross-border tax and compliance.
Rather than pursuing full automation, the platform is designed around governance, professional oversight, and decision traceability — aligning AI capabilities with the realities of regulated environments.
Cross-border tax and compliance workflows are fragmented across jurisdictions, advisors, and disconnected tools.
This fragmentation increases error rates, delays professional review, and disproportionately impacts individuals and small firms without access to institutional compliance infrastructure.
AskTaxly is the platform implementation of this initiative, designed to operationalize AI-assisted intake, validation, and professional review within real-world compliance workflows.
The system emphasizes structured data capture, exception handling, and review workflows rather than opaque end-to-end automation.
I lead problem definition, system architecture, and compliance-oriented design decisions, drawing on my background in finance governance, enterprise systems, and regulated operating environments.
Complexity in cross-border tax and compliance disproportionately affects skilled workers, international students, and small organizations, increasing noncompliance risk and limiting economic participation.
Improving access to structured guidance, compliance readiness, and professional workflows supports workforce mobility, regulatory adherence, and more efficient participation in the economy.