AI geoscience for critical mineral discovery.
DepoDart ingests any geoscientific data format, runs machine learning prospectivity models across your area of interest, and returns ranked drill targets with uncertainty bounds — in days, not months. No data migration. No minimum dataset size.
Three ways to work with DepoDart.
Exploration Projects
These are short-, medium-, or long-term exploration projects in which mineralization targets are identified through the integration of artificial intelligence and geoscience. Each project is carefully tailored to the geological context of the area of interest, enabling the accurate delineation and ranking of prospective mineralized zones.
The primary deliverables are high-resolution 2D and 3D geochemical prospectivity maps. In addition, DepoDart generates a range of complementary products, including lithological maps, structural geology interpretations, and geophysical variable models.
A key differentiator of our approach is explainability. Every prediction is accompanied by a narrative interpretation that describes the geological, geochemical, and geophysical factors contributing to the result, providing transparency and confidence in the targeting process.
Results can be delivered in a variety of formats; however, the most powerful option is an interactive software platform that enables users to visualize, explore, and analyze all associated data and interpretations in a single environment.
One of the platform's most innovative features is its adaptability. Users can customize and extend its functionality through natural-language prompts, allowing the system to generate new visualizations and analytical tools on demand based on user-defined requirements.
Interactive Data Preprocessing Tools
This software platform is designed to visualize, transform, and reformat geological datasets. It provides a comprehensive suite of statistical data-quality and preprocessing tools that can be applied either manually or through automated workflows.
For large datasets, users can configure and execute automated processing pipelines by selecting from a range of predefined actions. In addition, the platform enables users to create custom preprocessing operations through natural-language prompts.
These prompts are automatically translated into executable code, generating new tools tailored to the user's specific requirements. This capability allows geoscientists and data professionals to rapidly extend the platform's functionality without traditional software development, creating customized workflows that adapt to the unique characteristics of each project.
Free Online Regional Target Identification
This AI-powered mineral exploration platform leverages publicly available geological, geochemical, geophysical, and remote sensing data to identify prospective mineralization targets at a regional scale.
The application assists exploration teams during the early stages of target selection by generating two-dimensional prospectivity maps that delineate areas with the highest probability of hosting elevated concentrations of one or more commodities. In addition to target maps, the platform provides supporting geological insights and contextual information to facilitate exploration decision-making.
The system is continuously updated as new public datasets become available, ensuring that prospectivity models incorporate the latest information from government surveys, geological agencies, and other public data providers.
Users can also enhance the platform's predictive capabilities by uploading their own proprietary datasets through the web interface. These custom data sources can be integrated with public information, resulting in more refined and project-specific targeting outcomes.
Three-stage platform pipeline.
Data Fusion
DepoDart ingests and normalises multi-source geoscientific data regardless of format, coordinate system, or age. Drill logs, geophysics, geochemistry, satellite imagery, and structural maps are resolved into a unified spatial model automatically — no manual preprocessing required.
- Any coordinate system
- Legacy format support
- Conflict resolution
- Automated QC
AI Prospectivity Mapping
Our models learn the geological signature of known mineral deposits within your dataset, then apply that learned pattern across the full area of interest. Every point on the map receives a ranked mineralisation probability score, producing a continuous prospectivity surface at district scale and below.
- Supervised ML
- Multi-commodity
- District to deposit scale
- Probability surface output
Ranked Drill Targets
Every output includes a prioritised list of drill targets with confidence tiers, estimated depths, mineral type classifications, and uncertainty bounds. Full data provenance is included so your geologists can audit and defend every recommendation — no black-box outputs.
- Ranked priority list
- Uncertainty quantification
- Estimated depth
- Full provenance
Any format. Any vintage. Any coordinate system.
Clients deliver what they have. DepoDart resolves format conflicts, reprojections, and schema mismatches internally. There is no minimum dataset size or required preprocessing.
Geophysics
- Airborne magnetics (XYZ, GDB)
- Gravity surveys
- EM (ground/airborne)
- IP/resistivity
- Radiometric
Geochemistry
- Rock samples (CSV, XLS)
- Soil / sediment samples
- Assay tables (any schema)
- Lithogeochemistry
- Stream sediment
Geological
- Drill logs (LAS, CSV, DLOG)
- Geological maps (SHP, GDB)
- Lithology logs
- Structural interpretations
- Core imagery
Remote Sensing
- Multispectral (GeoTIFF)
- Hyperspectral
- SRTM/DEM elevation
- Landsat / Sentinel
- SAR derivatives
Four deliverables. Every pilot.
Prospectivity surface
Color-coded raster (GeoTIFF) showing ore-forming probability per pixel across the area of interest, exportable at any resolution.
Ranked drill targets
Prioritised CSV and PDF report of top drill locations with probability scores, mineral type, estimated depth, and confidence tier.
Uncertainty map
Companion raster quantifying model uncertainty per pixel — highlights where confidence is high vs. where more data would help most.
Data provenance report
Full audit trail showing which input layers drove each recommendation — critical for defensible exploration campaign planning.
One model. Every element.
The platform is commodity-agnostic. A single model run can score multiple commodities simultaneously without retraining. Current active targets include:
- Copper
- Gold
- Lithium
- Cobalt
- Nickel
- Silver
- Uranium
- Iron
- Manganese
- Zinc
- Rare Earth Elements
- Platinum Group
One pilot. Real data. A map you keep.
Share a dataset, and we return a prospectivity surface over your area of interest within days — with full data provenance included. No long-term commitment required.