ESGold's AI-Enhanced 3D Model Reveals Continuous Mineralized Zones at Montauban Project

ESGold Corp. (CSE: ESAU) (OTCQB: ESAUF) has announced the partial completion and interpretation of a comprehensive three-dimensional geological model of its flagship Montauban Gold-Silver Project in Québec. The AI-enhanced model revealed continuous, stacked mineralized zones defining multiple gold and silver-rich sulphide horizons extending beyond historical mine workings. According to the company's CEO and Director, Gordon Robb, the metamorphic overprint identified provides the geological backbone to explore Montauban as a true district, demonstrating that the property is the nucleus of a potentially much larger gold, silver, and base-metal district.

The Montauban model represents the most significant technical milestone in the project's modern history, transforming what was once seen as a series of small, isolated deposits into what now appears to be a continuous multilayered mineral system with dimensions not previously recognized. This discovery fundamentally changes the exploration potential of the property, suggesting it may host substantially more mineralization than historical records indicated. The identification of continuous mineralized zones stacked vertically provides multiple exploration targets within a single geological framework, potentially reducing exploration risk while increasing the probability of discovering additional economic mineralization.

For investors and stakeholders, this development represents a substantial advancement in understanding the property's true potential. The latest news and updates relating to ESAUF are available in the company's newsroom at https://ibn.fm/ESAUF. The comprehensive three-dimensional modeling approach, enhanced by artificial intelligence, allows for more precise targeting of future drilling campaigns and resource estimation work. This technological advancement in mineral exploration demonstrates how modern geological modeling techniques can reveal previously unrecognized potential in historical mining districts, potentially leading to more efficient discovery and development of mineral resources.

The implications extend beyond ESGold's specific project, showcasing how AI-enhanced geological modeling can transform exploration strategies across the mining industry. By identifying continuous mineralized systems rather than isolated deposits, companies can potentially develop more comprehensive mining plans and better understand the true scale of mineral resources. This approach may lead to more efficient resource development and potentially lower operating costs through better understanding of geological controls on mineralization. The discovery that the property represents the nucleus of a larger mineral district suggests significant upside potential for resource expansion and future development opportunities.