AI geologist

AI geologist

AI geologist

We are building a discovery engine for critical and precious metals — an AI system that turns fragmented geological data into high-conviction exploration targets for mining companies

We are building a discovery engine for critical and precious metals — an AI system that turns fragmented geological data into high-conviction exploration targets for mining companies

X marks the spot

X marks the spot

X marks the spot

We help mining companies find the next resource before they spend their next $50 million drilling the wrong targets.

We help mining companies find the next resource before they spend their next $50 million drilling the wrong targets.

Already successfully deployed in a gold mining company

“We would not have thought of that spot until the AI Geologist showed to us. At first we couldn’t believe it, but now we’re starting to drill.”

Chief Geologist (Gold mining major in TOP 20 mining companies)

“We would not have thought of that spot until the AI Geologist showed to us. At first we couldn’t believe it, but now we’re starting to drill.”

Chief Geologist (Gold mining major in TOP 20 mining companies)

15

Gold deposits found with Al; Checked and validated by certified geologists

15

Gold deposits found with Al; Checked and validated by certified geologists

20 000

Hours invested into building the technology

20 000

Hours invested into building the technology

Mineral exploration
is risky

Exploration teams spend years combining fragmented datasets, interpreting incomplete signals, and making high-risk drilling decisions with limited confidence.

Atlas Mining introduces a data-driven approach to geological targeting.

Exploration teams spend years combining fragmented datasets, interpreting incomplete signals, and making high-risk drilling decisions with limited confidence.

Atlas Mining introduces a data-driven approach to geological targeting.

$250M

Average cost of exploration for an economically viable mineral deposit, before a mine is established.

$250M

Average cost of exploration for an economically viable mineral deposit, before a mine is established.

0.07%

Probability of finding a world-class deposit.

0.07%

Probability of finding a world-class deposit.

20-25000

Projects investigated before a good-enough location found.

20 – 25 000

Projects investigated before a good-enough location found.

12 years

Average time between initiating exploration and exploitation of land.

12 years

Average time between initiating exploration and exploitation of land.

Actionable mining intelligence,
not just predictions

Actionable mining intelligence,
not just predictions

Actionable mining intelligence,
not just predictions

AI Geologist generates practical outputs designed to support real exploration decisions.

AI Geologist generates practical outputs designed to support real exploration decisions.

Deposit coordinates

Deposit coordinates

Pinpoint likely deposit locations

Depth and Orebody shape

Depth and Orebody shape

Understand target depth before drilling

Mineral Quantity and Quality estimation

Mineral Quantity and Quality estimation

Assess potential scale

Mineral classification

Mineral classification

Gold, copper, lithium, rare earths, etc.

Certainty score

Certainty score

Confidence-based prediction system

Geological reasoning

Geological reasoning

Transparent model-backed explanation

How AI Geologist turns data into targets

Book a Demo

  1. Data ingestion

The model ingests multiple layers of geological and contextual data: maps, satellite imagery, geochemical readings, magnetic surveys, and structural data.

2. Training

Training uncovers the geological patterns and correlations that signal mineralization, adapting to the unique terrain and conditions of each site.

  1. Target generation

Each generated target arrives with precise coordinates, depth, quantity, mineral type, a certainty score, and explainable geological reasoning.

How AI Geologist turns data into targets

Book a Demo

  1. Data ingestion

AI Geologist ingests multiple layers of geological and contextual data, including maps, satellite imagery, geochemical data, magnetic and structural data.

2. Training

The system identifies hidden geological patterns and correlations across complex terrains. Machine learning models evaluate the probability of mineral presence, depth, quantity, and geological context.

  1. Target generation

The product generates actionable mineral targets with coordinates, confidence scoring, and explainable geological reasoning.

How AI Geologist turns data into targets

Book a Demo

  1. Data ingestion

AI Geologist ingests multiple layers of geological and contextual data, including maps, satellite imagery, geochemical data, magnetic and structural data.

2. Training

The system identifies hidden geological patterns and correlations across complex terrains. Machine learning models evaluate the probability of mineral presence, depth, quantity, and geological context.

  1. Target generation

The product generates actionable mineral targets with coordinates, confidence scoring, and explainable geological reasoning.

data

Trained on 500 000 km² of scientific rigor

Trained on 500 000 km² of scientific rigor

Trained on 500 000 km² of scientific rigor

AI Geologist combines diverse geological datasets into a unified intelligence layer, allowing exploration teams to evaluate opportunities with greater depth, quality, and context.

AI Geologist combines diverse geological datasets into a unified intelligence layer, allowing exploration teams to evaluate opportunities with greater depth, quality, and context.

Geological maps
Geological maps

Detailed surface and subsurface mapping

Detailed surface and subsurface mapping

Geochemical data
Geochemical data

Comprehensive assay and geomestry

Comprehensive assay and geomestry

Satellite imagery
Satellite imagery

High-resolution multi-spectral data

High-resolution multi-spectral data

Designed for exploration teams and mining decision-makers

Designed for exploration teams and mining decision-makers
AI-driven exploration
AI-driven exploration

Prioritize high-potential targets before committing limited exploration budgets.

Prioritize high-potential targets before committing limited exploration budgets.

Major mining operators
Major mining operators

Screen large territories and accelerate early-stage opportunity evaluation.

Screen large territories and accelerate early-stage opportunity evaluation.

Exploration consultants
Exploration consultants

Use AI-generated intelligence to support client recommendations.

Use AI-generated intelligence to support client recommendations.

Geological teams
Geological teams

Combine fragmented data into a clearer targeting workflow.

Combine fragmented data into a clearer targeting workflow.

Reduce uncertainty before drilling

Reduce uncertainty before drilling

Faster targeting decisions

Move from raw data to clear target recommendations faster.

Better use of exploration budgets

Focus resources on higher-probability opportunities.

Explainable intelligence

Understand why each target was selected.

Scalable analysis

Evaluate multiple regions, datasets, or mineral opportunities with a repeatable process.

FAQ

FAQ

What type of data does AI Geologist need?

The system works best with layered geological data: geological maps, geochemistry, satellite imagery, magnetic maps, geophysical surveys, historical exploration reports and any existing drilling data. You don't need every layer to get started. The more complete and higher-quality the inputs, the stronger the prediction and certainty score.

Does AI Geologist replace geologists?

No. The system is built to support geologists, not replace them. It helps exploration teams narrow the search area, surface high-potential targets and understand why a location may be mineralized. The final call stays with your geologists, who review the evidence, weigh field conditions and decide whether to proceed.

Is the output explainable?

Yes. Every prediction is designed to show its reasoning. For each target, the system can explain which data layers drove the result, why the mineral may be present and the level of certainty behind it. The goal is a transparent decision-support tool, not a black-box answer.

Can it be used before drilling?

Yes, and this is one of the main use cases. The system helps prioritize where to explore first, cutting the number of low-probability targets so fieldwork, sampling and drilling budgets focus on the most promising ground.

Is this only for gold exploration?

No. Gold is one of the first use cases, but the system isn't limited to it. Support is being developed for copper, iron, cobalt and rare metals. Performance depends on the available data, the geology of the region and whether the model has enough relevant training information for that mineral system.