IGM combines field geology, geochemistry, geophysics and artificial intelligence into one connected exploration capability — from early-stage targeting to resource evaluation.
Our capabilities span the complete geoscience workflow: integrating geological, geochemical and geophysical data, applying AI-driven interpretation, and delivering the maps, targets and evaluations that guide real exploration decisions.
Machine learning models purpose-built for exploration data — from K-Coefficient terrain-ruggedness classification to LogPlot's automatic conversion of raw geological logs — turning field and remote-sensing data into interpretable targets faster than manual workflows.
Geological, geochemical and geophysical evidence — magnetometry surveys, sampling programs, structural mapping — combined into prospectivity models, with datasets managed and correlated through our GeoNA platform.
Field mapping, structural and stratigraphic analysis and geochemical sampling, informed by multi-source, multi-resolution remote sensing and delivered as thematic maps under our SUTGM mapping system.
Trenches, exploration boreholes and systematic sampling programs, carried through to reserve estimation and evaluation reporting for operational exploration and mining projects.
How those four capabilities get applied, project to project.
Every engagement runs on the same technical stack — our AI and machine-learning models, remote-sensing pipelines and in-house geospatial tools — applied consistently from first-pass targeting through to final reporting.
Where a project calls for it, we bring university researchers, partner institutions and international scientific networks directly into the exploration workflow — the same collaborations behind our published research.
Target selection and field programs are designed to reduce unnecessary ground disturbance and sampling, so exploration effort concentrates on the areas the data actually supports.
Where clients want it, we hand over method as well as results — training field and technical teams on the mapping, sampling and interpretation workflows we use ourselves.
