In today’s data-driven research landscape, access to high-quality identity records is critical for developing secure systems, fraud prevention tools, and AI-based verification models. However, real identity data carries serious risks—privacy breaches, legal consequences, and ethical concerns. That’s where synthetic data plays a transformative role. By allowing teams to work with statistically realistic yet fully artificial records, engineers and scientists can test, train, and validate algorithms without risking exposure of personal information. This approach is especially valuable when working with sensitive passport datasets, where even a small leak could lead to major legal and security issues. Using generated passports instead of real ones ensures compliance with data protection frameworks across the globe while still delivering practical usability for research and development.