How We Work - Methodology

An 8-stage validated pipeline that covers the entire mineral exploration lifecycle - from your first legacy map to a bankable resource report. Every stage is auditable, every parameter documented, every result traceable.

Two engines: GeoSwarm (cross-domain detection) + GeoThinker (probabilistic modeling).

1. What is CoreElement.AI

CoreElement.AI is an AI-powered platform for mineral exploration. It covers the complete cycle - from raw geological data to a finished resource report - in a single environment.

In practical terms: you have geological data (surveys, drillholes, maps, lab results) and you need to turn it into a clear picture of what's underground and how much it's worth. CoreElement.AI does this faster and more accurately than traditional workflows, because every tool you need is already built in and an AI assistant helps you at every step.

The platform generates Competent Person reports under all major international standards: JORC (Australia, ASX), NI 43-101 (Canada, TSX), KAZRC (Kazakhstan, KASE), SAMREC (South Africa, JSE), PERC (Europe), and CRIRSCO (international). It replaces the need to shuttle data between multiple specialised programs - Leapfrog, Vulcan, Surpac, Micromine, GIS packages, spreadsheets - everything happens in one validated database with 19 integrated modules.

    Core principle: Single Source of Truth. From the first magnetic survey to the final report - all data lives in one database. No CSV exports between programs, no version conflicts between departments. One database, one source of truth, full traceability of every action.
  

2. Your Data - Our Starting Point

Exploration projects typically accumulate decades of data: geophysical surveys, drillhole logs, geochemical results, geological maps, satellite imagery, historical reports. This is an enormously valuable asset - but only if it can be brought together and analysed as a whole. CoreElement.AI ingests all standard geological data types:

DATA TYPE	WHAT WE INGEST	STATUS
Aeromagnetic Surveys	TMI, RTP, analytic signal grids. GDB, GRD, XYZ, CSV, GeoTIFF	Supported
Radiometric Surveys	K, U, Th channels, total count. GDB, CSV, XYZ, GeoTIFF	Supported
Electrical Surveys (IP/Res)	IP / resistivity pseudosections, inversion results. GDB, CSV, UBC, Res2DInv	Supported
Gravity	Bouguer anomalies, regional/residual separation. GDB, XYZ, CSV	Supported
Aerial / Satellite Imagery	Orthophotos, multispectral (Sentinel-2, Landsat, ASTER), DEM. TIFF, ECW, JP2	Supported
Drillhole Data	Collar, survey, assay intervals, lithology, alteration, density. CSV, XLS, acQuire, Fusion, MX Deposit	Supported
Geochemistry / Sampling	Stream sediments, soil, rock chips, trench. Multi-element ICP-MS/OES, fire assay. CSV, XLS, ALS/SGS/BV lab formats	Supported
Hydrogeology	Groundwater levels, yields, chemistry, pump tests. CSV, XLS	Supported
Geological Mapping	Maps, sections, plans, structural data. SHP, DXF, KML, GeoJSON, PDF	Supported
Seismic / EM Data	SEG-Y, ASEG-GDF, EDI, TEM/FDEM profiles. CSAMT	Supported
Soviet-Era Legacy Data ★	GKZ reports, handwritten logs, maps in SK-42 / SK-63 / Pulkovo-42 coordinate systems, scanned technical reports in Russian. PDF, TIFF, JPEG scans - OCR digitisation built in	★ Unique

Soviet-era data - a unique capability. Many projects in Central Asia, Africa, and Eastern Europe sit on decades of exploration data collected under the Soviet geological system: handwritten logs, maps in SK-42 / SK-63 coordinates, resource categories A, B, C₁, C₂, P₁-P₃. Most modern platforms simply cannot read this data - they were designed for Australian and Canadian workflows and have no concept of Soviet coordinate systems or classification schemes. CoreElement.AI can. The built-in Historical Data & OCR module digitises scanned Soviet-era reports, automatically converts coordinate systems to WGS-84 / UTM, and maps GKZ categories to their JORC / NI 43-101 / KAZRC equivalents with fully documented rationale. This alone can save months of manual work and unlock value from historical datasets that would otherwise stay locked in paper archives.

50+ data formats are supported in total. The platform validates all incoming data automatically: checking coordinate systems, units of measurement, duplicate entries, gaps, and outlier values. If data was digitised manually from historical reports, the AI flags potential transcription errors.

3. The Pipeline: 8 Stages from Data to Report

Our methodology is a strict sequential pipeline. Each stage produces a validated result that feeds into the next. No stage can be skipped. At every point, the data and decisions are documented for Competent Person review and external audit. The AI Geologist is available throughout - ready to explain, suggest, and check your work.

PROJECT SETUP & HISTORICAL DATA

Create your project, define the licence area, and bring in everything you already have. The Portfolio Dashboard gives a bird's-eye view across all your projects: status, key metrics, team access. The AI Peer Analysis module automatically compares your deposit with analogues worldwide - similar geology, commodity, deposit type - so you understand the context from day one. If you have historical reports (including Soviet-era GKZ documentation), the Historical Data & OCR module digitises scanned pages, extracts tables, and converts legacy coordinate systems (SK-42, SK-63, Pulkovo-42) to WGS-84 / UTM automatically.

01 Portfolio Dashboard02 AI Peer Analysis04 Historical Data / OCR

DATA INGESTION & VALIDATION

All your data - geophysics, drillholes, geochemistry, imagery - is loaded into the unified database. The Drillhole Database structures collar, survey, assay, and lithology data with automatic validation: the system blocks overlapping intervals, impossible depths, and duplicate hole IDs. The Core Upload & Analysis module lets you photograph drill core directly from the core shed; AI assists with lithological classification and identification of mineralised intervals. The Geophysical Data Lake brings together all survey data - magnetics, radiometrics, IP/resistivity, gravity, EM - into one queryable repository. If you need additional field surveys, the Field Survey Ordering module lets you request quotes from service providers directly within the platform.

03 Drillhole Database05 Core Upload & Analysis06 Field Survey Ordering07 Geophysical Data Lake

AI ANALYSIS & ANOMALY DETECTION

This is where the AI earns its keep. Machine learning models analyse all loaded geophysical data simultaneously - magnetic, radiometric, electrical, gravity, satellite - and identify anomalies that may indicate mineralisation. The Anomaly Analysis module ranks each anomaly by confidence score, distinguishing geologically significant patterns from noise. The AI Prospectivity Map integrates all data layers (geology, geochemistry, geophysics, structural) into a single probabilistic model showing where target mineralisation is most likely. Think of it as a heat map of exploration potential - the warmer the zone, the higher the probability of a discovery. The geologist validates all results: AI proposes, the human decides.

08 Anomaly Analysis09 AI Prospectivity Map

3D MODELLING & DRILL PLANNING

The platform builds a three-dimensional model of the subsurface. The 3D Subsurface Viewer renders drillholes, geological surfaces, grade shells, and block models in an interactive environment - rotate, slice, zoom. Based on this model, the AI Drill Targeting module proposes optimal drill collar locations: coordinates, azimuth, dip, planned depth. The algorithm maximises geological information per metre of drilling while respecting budget constraints. The Uncertainty & Confidence module quantifies how reliable each part of the model is: where data is dense, confidence is high; where data is sparse, the model tells you honestly. The Drill Coordinates module exports final drill plans in formats ready for the field crew and survey contractors.

10 3D Subsurface Viewer11 AI Drill Targeting12 Uncertainty & Confidence15 Drill Coordinates

FIELD OPERATIONS & REAL-TIME MONITORING

When drilling begins, the platform connects to your operation in real time. The Drill Telemetry module receives live data from downhole instruments (IMDEX, Devico, Reflex): rate of penetration, weight on bit, survey readings (azimuth, inclination). You can monitor all active rigs from a single dashboard. The Core Laboratory module tracks every sample through the analytical pipeline - from the moment core leaves the hole to the final assay certificate. QA/QC control samples (standards, blanks, duplicates) are inserted automatically and monitored in real time. If a batch fails quality control, you know immediately - not weeks later when the resource model is already built.

13 Drill Telemetry14 Core Laboratory

RESOURCE ESTIMATION

With validated drillhole data in the database, the system builds a block model and performs geostatistical grade estimation. The Resource Estimation (JORC) module supports all standard methods: ordinary kriging, simple kriging, indicator kriging, inverse distance weighting (IDW), and nearest neighbour. The geostatistician configures variogram parameters (structure type, nugget, ranges, anisotropy), search ellipse geometry, and estimation domains. Mineral resources are classified into Measured (highest confidence - close drill spacing, reliable grade continuity), Indicated (moderate confidence - reasonable data density), and Inferred (lowest confidence - limited data, geological extrapolation) following the CRIRSCO framework. Results are validated through swath plots, visual section checks, global mean comparison, and change-of-support analysis. Every parameter, assumption, and decision is logged and auditable.

16 Resource Estimation (JORC)

ECONOMICS & REGULATORY COMPLIANCE

Once the resource is estimated, the platform helps you understand its economic value and regulatory path. The ROI & Economic Model calculates key metrics: net present value (NPV), internal rate of return (IRR), payback period, and operating cost per tonne. You can run scenarios - different commodity prices, mining methods, processing routes - to understand sensitivity. The Regulatory Timeline module tracks all permits, approvals, and compliance milestones specific to your jurisdiction - whether that's Kazakhstan, Australia, Canada, South Africa, or elsewhere. It tells you what you need, when, and the current status of each item.

17 ROI & Economic Model18 Regulatory Timeline

REPORT GENERATION

The final stage. The Report Generator assembles all project data, models, and analyses into a structured technical report following the required standard: JORC Table 1, NI 43-101 Form 43-101F1, KAZRC, SAMREC, or PERC. All sections are auto-populated from the platform database - no manual copy-pasting from spreadsheets. The AI Geologist drafts descriptive sections (geology, mineralisation, data quality) for the Competent Person to review. The CP reviews everything, adds commentary, and signs. Full traceability: who changed what, when, and why. The report is ready for submission to stock exchanges, regulators, investors, or banks.

19 Report Generator

At every stage of this pipeline, the AI Geologist is standing by - ready to explain what's happening, flag problems, suggest next steps, or draft report text. More on how this works below.

4. AI Geologist - Your Always-On Expert

Every screen in the platform includes the AI Geologist - an intelligent assistant trained on geological data, industry standards, and exploration best practices. This is not a generic chatbot. It understands geological terminology, your project context, and the specific data you're looking at right now.

What the AI Geologist Does

Explains what you see - on any screen, in plain language. If you're a geologist, you'll get technical detail. If you're an investor or project manager, you'll get a clear summary without jargon. The assistant adapts to your level.

Suggests next steps - which anomalies to prioritise, where to drill next, whether your QA/QC results look normal, what's missing from your dataset. It sees the whole project and can spot things a single specialist might miss.

Flags problems early - if your duplicate assays show systematic bias, if your drillhole surveys have suspicious deviations, if an entire batch of samples looks contaminated. The AI Geologist alerts you and suggests corrective actions before problems propagate into your resource model.

Helps write report sections - drafts descriptions of geology, mineralisation, data quality, and methodology for your Competent Person to review and sign. Saves weeks of writing while maintaining technical accuracy.

Speaks your language - the interface and the assistant work in English, Spanish, Portuguese, French, and Russian.

Crucially, the AI Geologist proposes - it does not decide. All final interpretations are made by the human geologist. The Competent Person (CP under JORC, QP under NI 43-101) retains full control and sign-off authority. This is a tool that amplifies expertise, not replaces it.

5. Quality Assurance & Quality Control

Data quality is the foundation of any resource estimate. If the input data is unreliable, no amount of sophisticated modelling can produce a meaningful result. CoreElement.AI embeds QA/QC at every stage - not as a separate step at the end, but as an integrated part of the workflow from the moment data enters the system.

1.Certified Reference Materials (CRM): Control samples with known certified grades are inserted into the sample stream. The system generates Shewhart control charts and automatically flags results outside ±2σ (warning) and ±3σ (critical - batch sent for re-assay). Standard practice: 1 CRM per 20-25 samples.

2.Field Duplicates: Repeat samples from the same intervals test reproducibility. The system generates Original vs. Duplicate scatter plots, calculates HARD (Half Absolute Relative Difference), and flags systematic deviations that could indicate sample preparation or splitting problems.

3.Blank Samples: Certified barren material inserted to detect contamination during crushing and pulverising. The system automatically flags any blank returning values above the analytical detection limit.

4.Umpire Laboratory: A portion of samples (typically 5%) is sent to an independent check laboratory. The platform compares primary and umpire results, identifies systematic bias, and calculates relative percent difference (RPD) between labs.

5.Point-of-Capture Validation: Drillhole coordinates, interval depths, and lithology codes are validated at the moment of entry. The system blocks overlapping intervals, impossible depths (from > to), negative lengths, and duplicate hole IDs. Invalid data cannot enter the database without an explicit geologist override and documented justification.

6.Full Audit Trail: Every action - from uploading a lab certificate to modifying a variogram parameter - is logged with user ID, timestamp, and justification. This is critical for Competent Person sign-off and external audit by regulators or stock exchanges.

    All QA/QC procedures comply with JORC Table 1 (Sections 1-2), NI 43-101 (Sections 11-12), and KAZRC requirements. The AI Geologist monitors QA/QC results in real time and alerts you to any failures before they propagate into your resource model.
  

6. Reporting Standards

CoreElement.AI generates technical reports under all major international public reporting standards. This means your project can be presented to investors, stock exchanges, and regulators in virtually any jurisdiction - from the same dataset, without re-doing any work.

STANDARD	JURISDICTION	APPLICATION
JORC 2012	Australia, ASX, Southeast Asia	World's most widely used mineral reporting code. Mandatory for ASX-listed companies.
NI 43-101	Canada, TSX / TSX-V	Canadian securities standard (CIM definitions). Required for all TSX-listed mining companies.
KAZRC	Kazakhstan, KASE	Kazakhstan public reporting code. Required for KASE listing and subsoil use reporting.
SAMREC	South Africa, JSE, SADC	South African code. Required for JSE listing. Common across sub-Saharan Africa.
PERC 2021	Europe, LSE, Euronext	European reporting standard. Used for LSE and Euronext listings.
CRIRSCO	International	The umbrella template unifying all national codes. Basis for mutual recognition between jurisdictions.

All these standards follow the same underlying classification system defined by CRIRSCO. Mineral resources progress from Inferred (lowest confidence, based on limited data) through Indicated (reasonable confidence, sufficient data for preliminary assessments) to Measured (highest confidence, based on detailed data with close spacing). Conversion to ore reserves - Probable and Proved - comes later, at the feasibility study stage, when mining, economic, and environmental modifying factors are applied.

Soviet GKZ → international standards: If your data uses the Soviet GKZ classification (categories A, B, C₁, C₂, P₁-P₃), the platform assists with conversion to JORC / NI 43-101 / KAZRC categories. Each mapping is documented with rationale - no "black box" conversions. Note that GKZ and CRIRSCO classification systems are not directly equivalent - the conversion requires geological judgement, not just a lookup table. For example, GKZ category C₁ may map to either Indicated or Measured depending on drill spacing and data quality. The AI Geologist guides the process, but the Competent Person makes the final determination.

7. Why CoreElement.AI

Single Environment

19 integrated modules in one platform. No switching between Leapfrog, Surpac, ArcGIS, Excel, and email. All data in one validated database - one source of truth.

AI Built for Geology

ML models purpose-built for mineral exploration: variogram fitting, geochemical pattern recognition, structural interpretation, geophysical anomaly ranking. Geology-native AI, not a generic tool repurposed.

Multi-Standard Reporting

One dataset → reports for JORC, NI 43-101, KAZRC, SAMREC, PERC. Switch reporting codes in one click. No re-work, no re-modelling.

50+ Formats + Soviet Data

Import everything: CSV, DXF, KML, SHP, GeoTIFF, LAS, ASEG-GDF, SEG-Y, and more. Plus full support for Soviet-era data, coordinate systems, and GKZ classification - a capability no other platform offers.

AI Geologist on Every Screen

A context-aware assistant that explains results, suggests next steps, checks data quality, and helps draft reports. Available 24/7 in five languages. Knows your project data inside out.

Full Audit Trail

Every data point, model run, parameter change, and decision is documented with user ID, timestamp, and rationale. Complete traceability for CP sign-off and regulatory audit.

8. Typical Project Timeline

Every project is different, but here is a representative timeline for a new engagement - from initial data handover to finished technical report.

PHASE	DURATION	WHAT HAPPENS
PHASE 1	2-3 weeks	Data Loading & Audit. You provide all available data: geophysical surveys, drillhole logs, assay results, satellite imagery, legacy reports. We ingest everything into the platform, validate, reproject coordinates, and build the project database. The AI Geologist reviews your dataset and flags gaps or potential issues.
PHASE 2	2-4 weeks	Analysis & Targeting. AI analyses all data, builds the prospectivity map, and proposes priority drill targets with coordinates, azimuths, and planned depths. You receive visual maps with probabilistic assessments and rationale for each target.
PHASE 3	Your schedule	Field Operations. You execute drilling on proposed targets. The platform receives data in real time: surveys, lithology, assay results. QA/QC is monitored automatically at every stage. The AI Geologist can flag unexpected results and suggest adjustments to the drill programme on the fly.
PHASE 4	2-4 weeks	Model & Report. 3D geological model, geostatistical resource estimation, and generation of the technical report (KAZRC / JORC / NI 43-101) depending on your requirements. Ready for Competent Person sign-off and submission to regulators, investors, or banks.

Total time from data handover to finished report: typically 8-14 weeks (excluding your drilling schedule). Traditional workflows with separate software packages commonly require 6-12 months for the same scope of work.

Ready to Start?

See the complete platform in action with real geological data from three exploration projects.

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