MINML provides AI‑driven mineral exploration by analyzing the entire subsurface at once, turning fragmented geoscience data into a coherent, explainable picture of ground prospectivity. Their platform identifies analogues to known ore bodies worldwide, ranks and scores targets, and validates predictions against expert‑mapped geology, enabling mining companies to focus on the most promising sites with confidence.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional mineral exploration relies on fragmented geological surveys and manual interpretation, making it difficult to identify undiscovered deposits hidden within vast, complex subsurface data. This leads to high exploration costs, low success rates, and missed opportunities for new resource development.
Solution
MINML uses a single AI-native model to ingest and integrate a century’s worth of geoscience data into a coherent, planet‑wide subsurface picture. By matching known ore bodies to their geological analogues worldwide, the platform ranks and scores every target, providing explainable prospectivity calls that improve as new discoveries are added. The model’s predictions are validated against existing mapped geology, ensuring confidence in unexplored areas. MINML backs its own prospect calls with direct stake ownership, aligning incentives and turning the prospectivity map into a tangible portfolio of mineral projects.
Target Audience
Primary customers are mining companies, exploration juniors, and resource investors seeking data‑driven identification and prioritization of new mineral deposits worldwide.
Features
- Unified AI model that reads the entire subsurface, combining diverse geoscience datasets into a single, searchable representation
- Analogue‑based search that identifies geological twins of known deposits anywhere on Earth
- Explainable prospectivity scores for each target, with underlying evidence presented for geologist review
- Automatic ranking and scoring of all global targets, producing a prioritized shortlist for investment
- Continuous model refinement where each new discovery sharpens predictions across all belts
- Direct stake ownership in the highest‑ranked targets, turning the prospect map into a revenue‑generating portfolio