Data & Analytics Platforms

AVEVA PI System (formerly OSIsoft PI System) is the dominant operations data management platform in heavy industry, deployed across 14,000+ sites in 127 countries. In mining, PI System serves as the system of record for all operational data — ingesting time-series data from process control systems, remote sensors, IIoT devices, and SCADA systems via hundreds of native connectivity options. Core components include PI Server (data archive and asset framework), PI Vision (browser-based visualisation dashboards), PI DataLink (Excel integration for ad-hoc analysis), Asset Analytics (streaming calculations), and Event Frames (contextual event capture for batch operations and shift reporting).

AVEVA Predictive Analytics uses machine learning to continuously monitor critical mining assets — crushers, mills, conveyors, pumps, and rotating equipment — learning normal operating patterns from PI System data and flagging anomalous behaviour before it results in unplanned downtime. The system builds digital profiles of healthy equipment operation and alerts maintenance teams when actual performance deviates from expected behaviour, providing lead time for planned intervention.

AVEVA Unified Operations Center (UOC) provides a comprehensive visualisation and situational awareness platform that integrates data from SCADA, PI System, ERP, and other business applications into a single enterprise-wide view. For mining, this means real-time visibility across extraction, processing, transport, and logistics — enabling collaborative decision-making and rapid response to operational events.

BeltMetrics Gen 2 provides continuous, non-contact particle size analysis on conveyor belts using stereo imaging and deep learning. It optimises crusher feed, detects empty belts indicating blocked chutes, measures transported material volume, and provides load profiling. As a critical mine-to-mill measurement point, BeltMetrics data in MetricsManager Pro closes the loop between blast fragmentation and processing plant feed.

brains.app is IntelliSense.io's core platform, delivering real-time decision intelligence across the entire mining value chain. The platform ingests, cleans, interpolates, and assimilates data from plant historians, sensors, and operational systems into a federated data lake, then applies hybrid physics-ML models to predict process behaviour and recommend optimal setpoints. Proprietary components include a Material Handling Model tracking metallurgical and physical properties in real time, a Data Quality Model ensuring only verified data feeds simulations, and a Reconciliation engine that reduces total data uncertainty. The platform uses Objective-driven AI with agents that propose actions, predict outcomes, and evaluate results against defined objectives, replanned every minute.

EarthNET was acquired through IMDEX's July 2025 purchase of Norway-based Earth Science Analytics for approximately A$26M. The platform provides cloud-native, AI-enabled ingestion and integration of diverse geoscience datasets — pre-drilling geophysical surveys, drillhole sensor data, core farm imagery, and laboratory results — enabling machine learning model application in a cloud-agnostic environment. Originally developed for oil and gas applications, EarthNET is being expanded into minerals and mining as the foundational platform for IMDEX's unified Digital Earth Knowledge ecosystem.

MaxMine Carbon leverages the platform's ultra-granular data to help open-pit mines measure, manage, and reduce Scope 1 diesel emissions. By analysing driver performance, payload efficiency, idle time, and driving patterns at high resolution, the platform enables mines to target and quantify emission reductions. MaxMine estimates that the average open-pit mine can reduce its carbon footprint by up to 20%, equating to approximately 30,000 tonnes of CO2 per year.

MaxMine Impact (also referred to as MaxMine Productivity) is the company's core product, integrating proprietary hardware data loggers (compatible with all surface mining OEMs), a cloud-based AI analytics engine called MaxCube, and a web-based analytics dashboard called MaxHub. MaxCube automatically cleanses, sorts, and classifies operational data using custom-built ML algorithms — free of human input — ensuring high accuracy in activity recognition, payload measurement, and performance scoring.

MetricsManager Pro is the analytics backbone of the Motion Metrics ecosystem. This web-based platform aggregates and analyses data from all installed hardware systems — ShovelMetrics, TruckMetrics, BeltMetrics, LoaderMetrics, and PortaMetrics — providing comprehensive reporting on particle size distribution, payload, tooth wear, boulder detection, and equipment performance. Users access data summaries, in-depth performance reports, automated SMS/email alerts (for missing teeth or oversized boulders), and cross-equipment analytics from any authorised browser.

Geminex is Metso's metallurgical digital twin platform, launched in March 2022 and winner of the Mining Magazine 2022 Software Award. It combines operational data from plant sensors and external sources with Metso's proprietary HSC first-principle process models — dynamic simulations calibrated with live plant data and continuously refined by machine learning algorithms. Unlike purely data-driven approaches, Geminex uses mechanistic models of physical and chemical processes, meaning it can produce reliable predictions even in operating regimes not previously encountered.

Metso Metrics is a cloud-based predictive maintenance and asset optimisation platform built on the Rockwell Automation FactoryTalk Cloud infrastructure and powered by Microsoft Azure. First launched in 2017 for aggregates and subsequently expanded to mining, it collects data from sensors embedded within Metso equipment — primary gyratory crushers, cone crushers, vibrating screens, and mills — and transmits it to the cloud for analysis.

MI Core is the foundational product of the Metallurgical Intelligence suite — a full plant digital twin that connects directly to source data systems and performs dynamic plant-wide mass and energy balance calculations every hour. The platform monitors inventory changes over time using machine learning, provides automated production reporting, tracks ESG emissions (Scope 1/2/3), and supports unlimited data source integration. MI Core V6 introduced parallel processing for 90% faster data import and 80% faster calculations.

MI Process Optimiser sits on top of MI Core, capturing data from millions of data points across the plant to identify optimum processing conditions using machine learning. The system handles time-lag dependencies (critical in minerals processing where cause and effect are often separated by hours), non-linear calculations, and multi-variable optimisation. It continuously learns plant operating patterns and compares theoretical optimal conditions against actual performance, quantifying the gap and recommending adjustments.

MineOne is a comprehensive digital platform that unifies data and workflows across the entire mining value chain. Rather than replacing existing systems, it integrates with third-party hardware and software — SCADA, PLCs, ERP, fleet management, CMMS — and presents a consolidated view through real-time 2D/3D dashboards, digital twins, and mobile field apps. Modules cover production management, fleet and asset tracking, workforce safety, environmental compliance, fuel management, and predictive maintenance.

MinePortal is a next-generation orebody knowledge platform acquired from DataCloud International in 2021 for approximately A$20M. It processes high volumes of geological and operational data in real time while applying geostatistical and ML algorithms to identify orebody trends and patterns. The platform enables real-time 3D geological visualisation accessible from any browser, eliminating the need for heavy desktop software.

MPX is a mine production software solution developed in Australia and deployed across surface and underground mining operations of various commodities. It delivers standardised, shift-by-shift production reporting covering KPIs, equipment utilisation, and material movements. MPX integrates operational data from across the mining value chain and serves as the trusted single source of truth for production performance, integrating with business intelligence applications for executive reporting.

Reconcilor is Datamine's flagship mine reconciliation software, automating the comparison of planned versus actual tonnes, grades, and metal production from resource model through drilling, blasting, hauling, stockpiling, and processing to final product. It highlights discrepancies and helps teams pinpoint dilution, ore loss, and operational inefficiencies that erode value. The platform features automated data import and validation, configurable reconciliation workflows, role-based dashboards, and audit-ready reporting.

Scenario provides operational and executive decision-makers with configurable KPI dashboards, data analysis tools, and compliance reporting. It delivers automated reports on demand or by subscription and supports critical-event notifications through SMS and email. As part of Datamine's production intelligence suite, Scenario transforms raw operational data into visual, actionable insights for mine management teams.

ShovelMetrics is Motion Metrics' flagship product, installed on over 250 shovels at 50+ mines worldwide. The Gen 3 version uses advanced high-definition bucket cameras with deep learning algorithms to provide missing tooth detection, tooth wear monitoring, lip shroud detection, payload estimation, particle size analysis, boulder detection, and operator blind spot reduction. All data flows to MetricsManager Pro for fleet-wide analytics and trend reporting.

Trakka is Dingo's flagship product — a single-platform solution that collects, analyses, and distils equipment data into actionable maintenance decisions. It integrates with ERP systems (SAP and others), OEM onboard monitoring systems, oil analysis laboratories, mobile field inspection devices, and CMMS platforms to create a unified view of asset health. The platform's proprietary analytics engine applies multivariate data trending, AI/ML failure prediction models, and a configurable Rules Engine for automated threshold management.