Mining

Transform your mining operations with AI-driven solutions that deliver measurable results

Real work. Measurable outcomes.

A snapshot of recent cases across mining and industrial clients - from predictive maintenance and centrally governed data platforms to AI-assisted quoting and Copilot upskilling.

Predictive MaintenanceOpen Surface Coal Mine

Predictive maintenance for mobile equipment using AI

As one of the largest coal producers in the US, the company operates more than 100 haul trucks. Equipment monitoring relies on oil samples, work orders, and telemetry alerts that are largely reviewed manually. Inconsistent oil analysis and alert overload make it difficult to identify degradation early, leading to reactive maintenance and costly unplanned component failures.

+80%

prediction accuracy for identifying upcoming mobile equipment failures

25%

reduction in unplanned maintenance costs for mobile equipment

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Data Quality & Field OperationsMining OEM

AI-assisted scan validation improving turnaround time and data quality

The OEM deploys field engineers globally to scan mining equipment using 3D scanners for asset health and utilization. Scan quality varies due to site conditions and setup, and issues are often discovered only after the engineer leaves. Poor scan quality leads to rework, manual correction, and slow turnaround from scan to final report.

Days → minutes

lead time from scan to final report

Higher

share of high-quality scans across sites and extended asset lifetime

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Data Platform & GovernanceMining Energy Company

Centrally governed data platform in Microsoft Fabric enabling analytics & AI at scale

The company operates multiple mines following acquisitions, with different equipment, systems, and data sources across sites. This fragments operational and financial data, making it difficult for management to gain consistent insights into maintenance and financial KPIs. At the same time, AI initiatives are driven locally, limiting scalability and group-level governance.

Central

visibility and control across mines and equipment

Scalable

centrally governed AI deployment across sites

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Customer Retention & MLOpsIndustrial Distributor

From churn-prediction pilot to fully automated AI in production on Azure

A global B2B industrial distributor had validated a customer churn AI model in a successful pilot, but the solution was maintained externally and run semi-manually. Retraining and inference required hands-on intervention each month, data extraction depended on a single internal owner, and recurring source-data quality issues forced constant firefighting - making it difficult to scale the insights across the commercial organisation.

Manual → fully automated

end-to-end pipeline from extraction to Power BI refresh

Production-ready

self-owned on Azure with logging, monitoring, and documented handover

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Sales Automation & Pricing AISpecialty Materials Distributor

AI-assisted quoting that cuts manual effort and standardises customer pricing

A Danish specialty materials distributor prepared customer quotes through a heavily manual process that consumed time from multiple people, including senior management. Each quote meant looking up current supplier prices, applying margin rules, factoring in fluctuating energy and gas costs, and drafting an offer by hand. The flow was slow, inconsistent between sales reps, and dangerously dependent on a few key people being available - making it difficult to respond quickly to customers or scale the business without adding headcount.

Hours → minutes

quote generation, from manual pricing work to instant AI-assisted recommendation

Key-person independent

quoting workflow no longer bottlenecked on senior staff availability

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Installed Base & Service GrowthIndustrial Machinery Manufacturer

Installed Base Proof of Concept unlocking the path from 7% to 13% service revenue

A Danish industrial machinery manufacturer wanted to nearly double its share of service revenue - from 7% to 13% of the business - but had no consolidated view of its installed base. Information about sold machines, components, service history, warranty status, and spare-parts needs lived scattered across Business Central, K- and R-drive folders, Excel sheets, and the heads of a few key employees. Service technicians arrived on-site without checklists, sales had no way to spot the highest-potential customers, and management could not steer the service business with reliable KPIs.

DKK 1.8–2.5M

near-term service revenue opportunity surfaced from a single installed-base use case

368 machines

consolidated into one Power BI source of truth, replacing Business Central, K/R-drive, and Excel silos

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AI Adoption & UpskillingIndustrial Machinery Manufacturer

Tailored Microsoft Copilot training that turned curiosity into daily AI use

Despite strong management ambitions to use AI strategically, day-to-day adoption inside the company was very low. Microsoft Copilot was available but rarely used, and teams across design, sales, service, and operations had no shared understanding of where AI could realistically help in their work. Without lifting baseline AI fluency, every other AI initiative - from the installed-base programme to future automation - would struggle to land.

+69%

increase in self-reported AI competence after training

+63%

increase in self-reported Copilot usage - many users moved from weekly to daily

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What we do

AI Consultancy

Strategic guidance and implementation support for AI initiatives.

AI Program Strategy Vendor & Technology Advisory Change Management Governance & Risk Management

AI Development

Custom AI solutions built for your specific operational needs.

Model Design & Architecture Proof of Concept & Pilots Productization & Scaling ML Ops, LLM Ops & DevOps AI Applications & Use Cases

Data Engineering

Robust data infrastructure to power your AI initiatives.

Data Infrastructure & Architecture Data Pipelines & Integration APIs & Interoperability Data Governance & Quality Visualization & Insights Enablement

Free resources for mining companies

Build an AI Decision Roadmap You Can Actually Stand Behind

A short assessment for executives that outputs a tailored roadmap, creating clarity on where you are and which decisions you are facing.

Open roadmap

Are you ready to identify which AI use cases are actually worth pursuing?

Identify 2–4 high-value AI use cases that are realistic to implement and aligned with where your organisation can create value first.

Start discovery

Why Predictive Maintenance Still Feels Reactive

Discover why critical equipment failures still arrive with little warning despite data collection.

Start diagnostic

Choosing Your First AI Use Case in Mining

How to move forward without starting a science project. A strategic guide for mining executives.

Read white paper

How Leading Mining Companies Manage Succession Risk

Protect decision quality across leadership transitions with a 5-minute diagnostic.

Start assessment

3 Cost Impacts of Reactive Maintenance in Mining

Discover the hidden cost impacts and how to move from firefighting to planned operations.

Read white paper

Why Predictive Maintenance Still Feels Reactive

Understand why failures still feel sudden despite having data and what must be in place.

Access white paper

Three low-hanging fruits most mining companies benefit from

ROI from the data you already have.

Process optimization

Leverage existing operational data to identify bottlenecks and inefficiencies in your production flow - delivering immediate improvements in throughput and resource utilization.

Predictive maintenance

Use equipment telemetry and maintenance logs to predict component failures before they occur - reducing unplanned downtime and extending asset life across your fleet.

Knowledge management

Transform internal documentation and expert knowledge into searchable AI assistants - ensuring critical operational insights are preserved and accessible to your entire team.

MineForward™ AI Program

Get started on your AI journey. We've bundled the three key elements that accelerate AI adoption in mining - from defining direction to scaling results.

Why This Program Works

Tech-Agnostic Approach

We're not tied to any specific technology or vendor. Our recommendations are based on what delivers real operational impact - not platform preference.

Leverage Existing Data

We build solutions using the data you already collect every day - transforming your existing systems into engines of measurable improvement.

Full Lifecycle Support

From early scoping and pilots to full-scale deployment, we provide end-to-end support to ensure lasting results, adoption, and ROI.

See how the program benefits you

Industry challenges

The mining industry faces a dual challenge - connecting operational realities with administrative priorities.

Administrative Challenges

Aligning data, systems, and decisions across the enterprise.

Siloed systems and inconsistent data quality

Manual reporting and lack of real-time visibility

Difficulty aligning strategy with field operations

Operational Challenges

Managing complex operations with limited predictability and high variability.

Failure to anticipate equipment breakdowns

Heavy reliance on individual expertise

Inefficient maintenance scheduling and reactive workflows

A curated, evidence-based library of publicly available AI implementations and inspiration cases across the mining value chain

Browse real-world cases. Refine by goal, data, equipment, or commodity.

Publicly Available Case

How BHP achieved $5.5M in annual savings through predictive maintenance for haul trucks

ML models trained on failure modes and telemetry prioritized risk-based maintenance. That cut unplanned failures and safely extended intervals.

BHP • Surface (iron ore) • 2023 • APAC

Saved $5.5M

Aplied.ai Case

How leadership teams could identify high-impact AI opportunities

Discovery workshops and data assessments deliver a prioritized AI roadmap with 8-10 opportunities.

Aplied.ai • Global Mining Organization • 2025 • Global

Publicly Available Case

How Rio Tinto achieved 15% cost reduction through autonomous haul trucks in the Pilbara

Komatsu AHS smoothed haul cycles and reduced idle time, delivering 700 additional hours per truck annually with zero safety incidents.

Rio Tinto • Surface (iron ore) • 2018 • APAC

15% cost reduction

View all 55 cases

You can filter AI cases based on data type, equipment, commodities and use case

Let's talk

Schedule a call to discuss how we can help your operations.

We're a team of AI consultants and engineers specialized in the mining & industrial industry. Our work focuses on helping companies unlock measurable value from their existing data - from predictive maintenance to operational optimization.