Lithosquare provides a cloud‑native platform that integrates geochemical, geophysical, remote‑sensing, and historic drilling data to generate AI‑driven predictive maps of mineral targets. Its deep‑learning models rank prospects by economic potential and quantify uncertainty, enabling explorers and mining companies to prioritize drilling and reduce costs. The solution includes an analytics dashboard with 3‑D visualizations and API connectors for seamless workflow integration.
Funding
Funding not disclosed
AFounders
Product
Problem
Traditional mineral exploration relies on labor‑intensive field campaigns and siloed datasets, resulting in long lead times, high drilling costs, and significant uncertainty when targeting critical mineral deposits. The slow pace hampers the ability to meet growing demand for strategic resources.
Solution
Lithosquare addresses these challenges by fusing foundational artificial‑intelligence models with deep geological expertise and extensive real‑world data. Its platform ingests geochemical, geophysical, remote‑sensing, and historical drilling data to generate predictive maps that rank prospective targets by economic potential. Advanced machine‑learning algorithms quantify uncertainty, allowing users to focus field effort on the most promising zones and reduce unnecessary drilling. Results are delivered through a cloud‑native analytics dashboard and an API that integrates with existing exploration workflows, accelerating discovery cycles while lowering overall project costs. The solution is built for scalability, supporting both junior explorers and large mining enterprises seeking to de‑risk critical‑mineral projects.
Target Audience
Primary customers are exploration divisions of major mining corporations, junior mining companies, and government agencies responsible for strategic mineral resource assessment. The platform is also valuable to consultancy firms that provide geological advisory services for critical‑mineral projects.
Features
- Multi‑source data fusion engine that combines geochemistry, airborne geophysics, satellite imagery, and legacy drill logs into a unified geospatial model
- Proprietary deep‑learning algorithms for target probability scoring and economic viability ranking
- Bayesian uncertainty quantification that highlights confidence intervals for each predicted target
- Cloud‑based analytics platform with interactive 3‑D visualizations, drill‑plan optimization tools, and automated reporting
- RESTful API and FME‑compatible connectors for seamless integration with GIS, mine‑planning software, and corporate data lakes
- Continuous model retraining pipeline that incorporates new field data to improve prediction accuracy over time
- Role‑based access control and end‑to‑end encryption to meet industry data‑security standards