Conventional mineral exploration involves an incremental, area reduction, decision-making process that, at best, uses 20‑40% of available data and is subject to human bias.

SensOre takes a different approach, applying integrated AI/ML algorithms to a large geoscience Data Cube to find the digital fingerprints and ‘predict’ the location of mineral deposits in three core steps: training, prediction and target analysis. In doing so, SensOre generates AI-targets (AI-enhanced deposit predictions) informing targeting.

SensOre’s exploration tools predict the location and economic viability of deposits, generating information on endowment (size), grade and depth at a cell dimension small enough to quicken decision making and move directly from predicted target to drill testing cost effectively and with a narrower environmental footprint.

SensOre works with partners and clients to unlock the value of geoscience data and the potential of new and existing exploration sites.

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We invest heavily in our Technology division, including our research and development program, to validate and enhance our technology assets and product suite. The technology currently deployed by our Exploration and Exploration Services divisions includes:


An AI-target generation and validation technology that uses Data Cube to make predictions regarding the location, size (i.e. endowment), grade (i.e. average ore concentration) and depth (i.e. metres to top and base of each deposit) of a given deposit.

Managed by SensOre, the SensOre Discoveries Database is an evolving repository of publicly available mineral deposits and occurrences data. This proprietary deposit database is a competitive advantage and a key part of predictive targeting in both prospectivity mapping and DPT.


A multidimensional repository of cleaned and levelled geoscience data. The Data Cube continues to expand as additional public and proprietary geochemical, geophysical and geological data is acquired by SensOre. The Data Cube contains over 2,500 data layers and +24 billion discrete data points.


The Archean Gold Lode Alteration Detection System (AGLADS®) is a machine learning system designed to identify alteration of various types (i.e. host, distal, proximal, ore) enveloping gold lode systems found in the Archean of Western Australia. AGLADS® is used as a geochemical ‘Vector to Gold Ore’ during routine exploration and evaluation work performed by SensOre, including the evaluation of drilling data.

igRock is a prototype rock-type classification system based on igneous rock type identification using multi-element geochemical assay data. The system is designed to identify igneous rocks predicted to be associated with, or host to, mineralisation that is of interest to SensOre and its clients.

Using multielement, geological and mineralogical data, iDeposit is an ore deposit type classification system derived from the geochemical signature of different deposit types.

iFertile is a geochemistry-based gold fertility prediction system designed to predict the total contained gold in a potential target from the data contained in a mineralised intersection.