If the earth has
measured it, we model it.
Mineluz was founded to revolutionize how natural resources are discovered. We combine leading AI research with deep geoscience expertise to turn months of work into days — raising success rates while cutting wasted effort.
Data-driven AI,
unlocking what's hidden.
The earth leaves a signal everywhere we look — seismic, magnetic, thermal, hyperspectral. Mineluz makes those signals computable in real time.
Innovative AI
Advanced models improve mineral prediction accuracy by integrating diverse datasets — precision and efficiency in every exploration decision.
Real-time seismic
Machine-learning algorithms improve seismic interpretation accuracy, reducing errors and costs significantly.
Cost & time efficiency
AI-driven drilling optimization reduces failures by up to 50%, dramatically lowering costs and boosting success.
Built by geoscientists
and ML researchers.
A short timeline.
Research lab
First 3D CNN fault-mapping paper accepted. Prototype trained on open SEG-Y corpus hit 0.85 IoU against hand-picked ground truth.
First pilot
Deployed with a major porphyry operator. 35% cost reduction inside six months.
Platform
Mineluz Core v1: unified ingest + inference + export. Three commodities supported.
v2.1 general availability
Transformer target ensembles, real-time confidence fields, and ArcGIS / QGIS sync.
Meet the team.
Lisa Palleson, PhD
CEO
Serial tech entrepreneur. PhD, International Business. Previously led global firms in cybersecurity and health; now steers Mineluz strategy.
Ravi Thapa, PhD
Chief Scientist
20 years in geophysics and ML. Author of the 3D CNN fault-mapping architecture that ships in Mineluz Core.
Marta Keller
Head of Platform
Built large-scale geospatial pipelines at two energy majors. Owns Mineluz's ingest and streaming stack.