Full vertical-AI mineral discovery platform

One intelligence network. From orbit to orebody.

MiningHub.ai orchestrates 1,200+ specialised AI tools across the complete mineral exploration stack, creating an interconnected mineral-discovery network in which every signal strengthens the next — and every conclusion remains traceable through the Glass Box.

Intelligence & historical records · satellite · airborne · drone · ground geophysics · field evidence · 4D subsurface modelling · drilling

Most AI is a black box. MiningHub.ai is a glass box.

Auditable, traceable mineral exploration AI: every satellite scene, geophysics survey, assay and drill target can be traced to its source and independently re-checked against JORC 2012 and NI 43-101 expectations.

Conventional AI platforms hand you an answer and ask for trust. MiningHub.ai shows its workings instead: every target, every grade, every interpretation can be opened up and traced back to the scene, sample or document that produced it — by your own team, or by a third party.

• Audited. Every automated decision is logged with its inputs, its evidence and its reasoning — a complete record, not a summary.
• Compliant. Work is structured against JORC 2012 and NI 43-101 expectations from the first observation, so reporting is an output, not an afterthought.
• Defensible. Where evidence is insufficient, the platform says so and stops. A conclusion that cannot be defended is never issued.
• Traceable. Any claim can be walked back to its source coordinates, documents and dates — and independently re-checked, step by step.

Built to be audited, not admired.

Defensible drill targeting for mineral exploration — provenance on every claim, and a conclusion withheld wherever the evidence does not support it. An exploration platform is only worth what its weakest inference is worth. MiningHub.ai is engineered so that a target either survives scrutiny or is discarded — and so that a third party can check the difference.

The problem: exploration knowledge is scattered across a dozen tools.

In conventional exploration workflows, imagery sits in one desktop GIS package and geophysics in another. Historic reports sit in a filing cabinet, assays in spreadsheets, and the interpretation in a consultant's head. Every handover between them loses provenance, and by the time a drill target is proposed, no one can reconstruct why. MiningHub.ai removes the handovers.

No single instrument finds an orebody. So we use them all.

A full vertical-AI mineral discovery stack: satellite and radar remote sensing, aeromagnetics and radiometrics, drone TEM, ground geophysics, field sampling, 4D subsurface modelling and drilling — fused, not sampled. Removing any layer degrades the answer, because the orebody lives in all of them together.

Remote sensing — the ground surveyed before anyone sets foot on it

Multispectral and radar coverage is processed into alteration mineralogy, structure and anomaly maps across an entire licence — not a hand-picked window. Powered by Sentinel-2 and Landsat data, fused with high-resolution aeromagnetic, radiometric, drone-borne TEM and ground surveys. Spectral indices resolve to mineral assemblages; lineaments, intersections and dilational sites are derived from terrain and magnetics rather than drawn by hand; and multi-epoch scenes separate real signal from disturbance, workings and seasonal artefacts.

Intelligent systems — a century of literature, read and reconciled

Government surveys, historic company reports, published assays and academic literature — much of it existing only as scanned paper, maps and handwritten logs — are read by machine, converted into structured data, geo-anchored and cross-checked against each other. Scanned reports, faded maps and tabulated assays are digitised, interpreted and extracted by machine learning, turning a century of paper into queryable evidence. Conflicting historic accounts are surfaced and weighted rather than averaged into a false consensus.

4D subsurface — a modelled orebody you can interrogate, not a picture of one

Surface evidence, geophysics and sample chemistry converge into a depth-resolved model of the mineral system — prospectivity volumes, alteration envelopes and drill targets with depth, orientation and the evidence behind each one. Volumes are built from observed anchors; nothing is synthesised to fill an empty corner of the model.

Drilling — the model earns its place in the ground

The entire stack converges on a single act: drilling. Ranked targets — each carrying its evidence, confidence, depth and the commodities actually being sought — drive the program design. As holes are drilled, results are recognised against prediction and assays flow straight back into the model, so every metre of core either confirms or corrects what came before.

On the ground — the model follows the crew into the field

Targets, traverses and sample points move from the model to the field team, and logging, chain of custody and assay results move straight back in — closing the loop between what was predicted and what was found. Sample registration, custody, QA/QC and laboratory reconciliation are held in one auditable record.

The guarantees, stated plainly.

• Evidence-anchored, never invented. Every interpretation must trace to a source document, sample or scene. Unsupported statements are rejected, not softened.
• Commodity-native units. Grades are reported in the units the commodity is traded in — no synthetic equivalence, no gold-converted framing.
• Contradictions surfaced, not averaged. Conflicting historic accounts are exposed and weighted, rather than averaged into a false consensus.
• Full-stack fusion. Orbit, air, drone, ground and sample in one chain. Removing any layer degrades the answer.
• Self-correcting by design. Conclusions are revised as new assays, scenes and surveys arrive, and every correction is dated and kept.
• Silence over speculation. Where the evidence is insufficient, no conclusion is issued. A target that cannot be defended is discarded, not dressed up.

Native, self-correcting, and sharper with every datapoint.

A browser-native mineral exploration platform that revises its own subsurface models and drill-target rankings as new assays, scenes and surveys arrive — every correction logged. There is nothing to install and nothing to license.

• Every run feeds the next. Each screening, interpretation and verified finding is written back into the platform's own evidence layer. The next prospect starts from everything the last one proved.
• Corrections are the engine. Where a reading is wrong, it is corrected, dated and kept. The platform does not overwrite its mistakes — it learns from them, and the record of that learning becomes part of the asset.
• Nothing is discarded. A negative result is still data; a dry hole still narrows the search. Across Inala's portfolio, every outcome sharpens the resolution of the whole.

The result is a self-healing mineral data corpus: compounding evidence that cannot be bought, only accumulated.

A private platform.

MiningHub.ai is built and operated by Inala Group for its own exploration portfolio and selected partners. It is not offered as a product. Introductions are welcome by direct contact via mininghub.ai.