Objective: Reduce exploration expenditure by 30–40%, accelerate time to discovery and strengthen portfolio expansion decisions through AI-driven mineral prediction.

Scenario: A copper–gold operator holds decades of drilling samples, geological surveys, geophysical datasets and production records; spread across multiple coordinate systems, formats and legacy platforms. Traditional exploration requires millions in new drilling and 12–18 months of lead time, delaying growth, increasing risk and weakening capital efficiency.

Product Solution: GX360 ingests and harmonises all historical and contemporary datasets [core samples, assay results, geophysics, structural geology and production data] regardless of format or reference system. Its transparent, auditable machine-learning models identify geological patterns and predict high-probability mineralisation zones at 50m³ resolution, creating a defensible, data-driven basis for investment decisions.

Output: A fully interactive 3D subsurface model displaying predicted mineral deposits with precise coordinates, estimated grade ranges (Cu %, Au g/t), tonnage forecasts and statistical confidence levels (e.g., 85% confidence for high-grade zones). The platform generates a ranked list of recommended drilling targets based on economic potential, enabling Boards and investors to prioritise capital with greater accuracy, speed and certainty.