Anomaly Detection

Analytical Methods

Geochemical data analysis with AI: explore multi-element assays in ioGAS, then add Python and ML scripts that cluster samples and flag anomalies for you.

Belt Sense

A conveyor belt analyzer like MineSense BeltSense reads ore grade on the belt in real time, so you can divert dilution or misrouted ore before the mill.

Geochemical Proxies

Use geochemical proxies with AI: train a model on known-deposit multi-element signatures, then run it on your data to map prospectivity, as VRIFY DORA does.

Geotechnical Monitoring

Geotechnical monitoring with AI runs slope radar (IDS GeoRadar) and satellite InSAR (SkyGeo) through ML layers so wall-failure warnings surface early.

Geotechnical Reports

Automate geotechnical reports by connecting Power BI or Tableau to your live geotechnical block model and monitoring feeds, so they regenerate on their own.

Hydrological Modeling

Make hydrological modeling AI-ready: script MODFLOW 6 in FloPy instead of a GUI, so the same pipeline can feed ML calibration and prediction workflows.

Monitoring during mining

Slope stability monitoring during mining: link piezometers, inclinometers and crackmeters to a platform like Worldsensing so AI flags abnormal trends.