Nevada Sunrise Identifies New Target Areas with VRIFY's AI-Assisted Mineral Discovery Platform at the Past-Producing Griffon Gold Mine Project, Nevada

Core Insights - Nevada Sunrise Metals Corporation has enhanced its partnership with VRIFY Technology Inc. to utilize DORA, an AI-Assisted Mineral Discovery Platform, for identifying new target areas at the Griffon Gold Mine Project in Nevada [1][2] Company Developments - The Company entered into a mining lease to acquire the Griffon Gold Mine Project in February 2025, which previously produced 62,661 ounces of oxide gold from 1998 to 1999 [1] - In March 2025, a partnership with VRIFY was announced to implement AI software for the Project, leading to the compilation and expansion of historical exploration data [2][9] - Nevada Sunrise plans to conduct soil gas hydrocarbon and conventional soil surveys, along with ground geophysical surveys in fall 2025 to validate findings and define future drill targets [5][6] Project Specifics - The Griffon Gold Mine Project is located approximately 50 kilometers southwest of Ely, Nevada, covering 89 unpatented mineral claims over 1,780 acres [11] - The project is situated within a gold-rich area known as the Battle Mountain-Eureka trend, which hosts several significant gold mines and deposits [11] - Historical data from the Griffon project includes surface geological, geochemical, and geophysical results, creating a comprehensive dataset for analysis [2][9] Exploration Plans - A Notice of Intent was submitted to the United States Forest Service in July 2025 for initial surface exploration plans, which received a positive response [6][7] - The exploration work will focus on areas identified by VRIFY's DORA platform, particularly the unmined "Anvil Zone" southwest of the Hammer Ridge pit [5][6] Technology Utilization - VRIFY's DORA platform allows for the integration of project-specific data with a large proprietary exploration dataset, enabling the identification of high-potential mineralization areas [8][9] - The platform's algorithms provide data-backed insights that would be challenging to extract through manual processes, enhancing exploration efficiency [9][10]