Your plant fails on its own schedule.
Now you can see it coming.
AI Surge turns the telemetry you already collect into pre-emptive action: catch a crusher, pump or conveyor failure before it costs you a shift, flag the near-miss patterns that precede a serious incident, and capture forty years of operator know-how before it flies out on the next roster change.
In mining and heavy industry, downtime is the most expensive number on the page.
It is 2am on nightshift. A haul truck is down with a failed final drive, the primary crusher is starving, and the ROM stockpile is dropping fast. The part is three days away in Perth, a week away if the freight slips. By the time dayshift walks through the gate you have lost more production than the repair will ever cost, and the crew is reacting instead of planning. The hardest part to sit with is this: the failure did not come out of nowhere. The signs were in the data. Nobody was watching the right number at the right time.
When a primary crusher, an overland conveyor or a dragline drops, it does not cost you a repair bill, it costs you the shift, six figures of lost production and a scramble for parts that sit weeks away on a remote site. A safety incident costs far more again: in people, in a Section 39 notice or a stop-work order, in the shutdown while the regulator investigates. And the know-how that prevents both sits in the head of the fitter who has read that gearbox by ear for thirty years and retires next roster.
You have already spent the money on condition monitoring, a historian and safety reporting. The vibration traces, the oil analysis, the take-five and near-miss reports, the PLC and SCADA tags, it is all being collected. What is missing is the layer that reads it together and says, in plain English: "this pump bearing fails inside 14 days unless we intervene," or "the vibration and temperature drift on CV-04 matches the profile that preceded the failure at the sister site eight months ago."
AI Surge builds that layer. We unify your historian, CMMS, control-system and safety data into one operating picture, embed models that flag failure and incident signals days or weeks before they surface, and capture the tribal knowledge of your senior operators so the next crew inherits four decades of judgement alongside the asset register. Australian and NZ based, no offshore handoffs, and where sovereignty demands it, running entirely on your own hardware.
A processing plant kept losing the same slurry pump to bearing failure every few months. Always mid-shift, always a scramble. Before: the vibration data sat in the historian, glanced at monthly if at all, and the first anyone really knew was the high-temperature trip and a starved circuit. After: a model trained on that same historian picks up the bearing signature climbing about 14 days out, raises a work order against the next planned window, and the pump is changed on a Tuesday dayshift with the spare already on the shelf. Same data, same crew, same pump. A failure turned into a scheduled job.
Predicted Ahead
Reduction
Downtime
and Preserved
Typical outcomes for Australian mining and heavy industry operators we work with. We model the numbers against your own operation before any build.
AI Platforms We Deploy in Mining
The right platform for each problem. We integrate what you need, nothing you do not.
Where AI Delivers Value in Mining
Concrete applications across the operation, from the pit and the crushing circuit to the planning office.
Predictive Asset Health
For the reliability engineer and maintenance planner: models trained on vibration spectra, bearing temperature, oil analysis and CMMS work-order history flag pump, motor, conveyor and crusher failures 7 to 21 days out. You move from reactive call-outs to planned interventions in scheduled windows, cutting maintenance cost 15-25% and unplanned downtime by up to 60%.
Pre-Incident Safety Signal Detection
For the site HSE lead: models trained on your incident history, near-miss and take-five reports and operational telemetry surface the patterns that precede an event, from a spike in a hazard category to drift in a critical control. An early-warning layer that complements your safety systems and human judgement without ever controlling plant.
Tribal Knowledge Capture
For the maintenance superintendent facing a wave of retirements: capture how your most experienced fitters and operators diagnose faults, work around quirks and read the plant, into a queryable system. The corner-case know-how that separates a smooth shift from a costly one stays on site after the person leaves.
Production Optimisation Across Constraints
For the mine planner and metallurgist: agents that sequence production across changing ore grades, equipment availability, energy pricing and crew rosters. Lift throughput and recovery from the fleet you already own, balancing blend and plant load without a dollar of additional capex.
Compliance and Environmental Reporting
For environmental and compliance teams: automate the reporting that eats their week. Pull emissions, energy, water balance and rehabilitation data straight from operational systems, draft the NGER and regulator submissions, flag exceptions and route for sign-off. Consistent and audit-ready across every site.
Shift Handover and Cross-Site Benchmarking
For superintendents and operations managers: AI-generated handover briefs that carry the full context from nightshift to dayshift so nothing is lost across a FIFO changeover, plus on-demand benchmarking that compares throughput, availability and cost across sites on the same definitions instead of a fortnight of reconciling spreadsheets.
Before AI vs. After AI
Typical outcomes across Australian mining and heavy industry operators in the first 12 months.
| Operational Area | Before AI | After AI |
|---|---|---|
| Crusher, pump and conveyor failure | Reactive call-outs, lost shift | Predicted 7-21 days ahead |
| Maintenance cost per asset | Calendar-based servicing | 15-25% lower, condition-based |
| Unplanned downtime | Absorbed as the cost of doing business | Reduced by up to 60% |
| Near-miss and incident signals | Reviewed retrospectively | Patterns flagged early for action |
| Retiring operator knowledge | Walks out the gate | Captured and queryable on shift |
| NGER and environmental reporting | Weeks of manual spreadsheet work | Days, mostly automated and audit-ready |
| Cross-site production benchmarking | Variable definitions, slow | Standardised and on-demand |
"The vibration data had been sitting in the historian for years. We just did not have the people to turn it into a call the maintenance planner could act on. That is exactly what this gave us, a fortnight of warning before a failure, without changing a single operator's day."Operations Director, Australian Mining Operator
From First Conversation to Live Platform in 90 Days
A structured path that starts delivering value before the platform is built.
Discovery Conversation
We map the fleet, the critical assets and the failures and safety risks that keep you up at night.
Site Assessment
A structured review of your historian, CMMS, SCADA and safety data, and the quality of the telemetry behind them.
Strategy and Roadmap
Prioritised use cases, an ROI model built on your own downtime and cost figures, and a sequenced 90-day plan.
Productivity Rollout
AI in the hands of planning, engineering and office teams inside the first month, while the platform is built.
Custom Platform Build
Predictive asset health, safety signal detection or knowledge capture, integrated with your historian, CMMS and control systems.
Continuous Optimisation
Quarterly reviews, model retraining against fresh failure data, and expansion to more assets and sites as the operation evolves.
Designed for Australian Mining Conditions
We work with mining and heavy industry operators across Western Australia's Pilbara and Goldfields, Queensland's Bowen Basin and Galilee Basin, New South Wales' Hunter Valley and South Australia's mining regions. Remote sites, fly-in fly-out rosters and constrained connectivity are the conditions we design for, not exceptions. Australian and NZ based, with no offshore handoffs.
Common Questions from Mining Operators
The operators investing in AI now will run leaner, safer sites than the ones that wait.
If you are the maintenance manager, superintendent or operations manager who gets the call when the plant goes down, this is built for your operation. Talk to us about predictive asset health, tribal knowledge capture or safety signal detection, and we will model the numbers against your own site before you commit to anything.
Book an Obligation-Free Consultation