AI agents for the mine you already run: fuel and equipment records reconciled as they happen, and every anomaly sent to a person.
Mirage Metrics builds and operates AI agents for mining and quarry operators. Delivery notes, tank probes, pump terminals and machine logs each hold part of the story. Mirage ties every transaction to a vehicle, a pump and a site, and every machine to its own maintenance intervals.
A fuel delivery is recorded on the supplier's note. The agent checks it against the tank probe, then follows the volume through the pump terminals to each vehicle's consumption. When the litres do not add up, the gap goes to the person who can act, with the delivery note, the tank readings and the pump transactions attached, while it can still be explained.
Tank probes, pump terminals, supplier delivery notes, telematics and machine logs, from the systems already on site.
Delivered volumes against tank stock and pump transactions, then against each vehicle's consumption.
Greasing, oil changes and mileage tracked per machine, and maintenance scheduled before a breakdown.
Missing volumes, suspicious transactions and abnormal usage go to the person who can act, while they can still be explained.
A Moroccan logistics operator moving mining, fertilizer, steel and agri-food freight with 550 specialized trucks and 100+ machines. It started with one document workflow.
Lower fleet diesel consumption
Systems live across freight, fuel, mining and fleet
Control room across the whole business
Transwin, from the case study's results.
“We started with one workflow, and Mirage has been alongside us at every step since. Every process we brought them, they built and put into production. Today they are not a supplier we buy software from. They are our AI partner.”
No forced migrations. Your data, our intelligence.
PI System
Where a documented interface exists, Mirage connects to it. Where none exists, our engineers build the connector during deployment.
The same five steps for every deployment, in every sector.
Engineers spend time with operational teams before writing anything, to see how work is actually done.
Time with the people who run the fleet, the equipment and the site.
Workflows, exceptions, data sources, manual validations and escalation points get identified with your team.
Your data sources, exceptions and the checks your team does by hand.
Systems get designed around the constraints observed on site, not an idealized process diagram.
Access to the systems you already run: fleet management, maintenance, telematics, geological databases.
The system runs in production with human supervision and feedback loops from day one.
People to review the alerts and recommendations routed to them.
Once a workflow is trusted, the same engineering team moves to the next one.
The next workflow you want to hand over.
Access permissions, validation workflows and audit logs remain fully controlled by your organization. Signed NDA on request.
Cloud, private cloud, your own cloud account, sovereign cloud, on-premise, or edge and offline environments.
Role-based access, human approval flows and configurable autonomy for each workflow.
Full audit history, with every agent action traceable to the input and the rule that produced it.
Each system operates on the same data foundation. Deploy one or all four, from first drill to full production.
Geoscience-driven mineral discovery. Identifies high-potential drilling zones by fusing geological, geochemical and remote sensing datasets into ranked prospectivity maps.
Continuous equipment health monitoring. Detects failure signatures before breakdowns occur and schedules maintenance at optimal windows.
Real-time haulage optimization. Continuously recalculates truck assignments, load factors and routing based on live production data.
Operational data aggregation across all mining systems. Surfaces anomalies, tracks KPIs, and connects field data to management decisions.
From exploration to extraction. The AI surfaces the signal, prioritizes opportunities, and detects anomalies. Geologists, engineers, and operations teams remain responsible for validation and operational decisions.
AI for mining operations is software that applies machine learning to geological data, equipment telemetry, and production records to identify mineral deposits, predict equipment failures before they occur, optimize fleet dispatch, and consolidate operational data into a single view. It replaces fragmented manual analysis with continuous automated intelligence across the full mining lifecycle.
The platform runs four agents simultaneously: an AI Exploration agent that maps prospectivity and identifies drilling targets from geological data, a Predictive Maintenance agent that monitors equipment telemetry and flags failure risk before breakdowns occur, a Fleet Optimization agent that maximizes utilization across the haul fleet, and a Production Intelligence agent that consolidates operational data across the site.
AI exploration systems process geological surveys, drill logs, geochemical data, and remote sensing data simultaneously to identify deposit patterns that manual analysis misses. They generate ranked prospectivity maps that prioritize drilling targets based on multiple data layers rather than single-indicator analysis. Operations typically reduce the number of unproductive drill holes by identifying higher-confidence targets earlier in the exploration program.
Predictive maintenance agents monitor real-time telemetry from haul trucks, excavators, crushers, and processing equipment. They detect anomaly patterns in vibration, temperature, pressure, and hydraulic data that precede failures by days or weeks. Maintenance is scheduled during planned production windows rather than triggered by breakdowns, reducing unplanned downtime and extending equipment lifespan.
The platform connects to all major mining operations systems on the market, including SCADA platforms, fleet management software, maintenance management systems such as SAP PM and Infor EAM, geological databases, and drill planning tools, through direct API integrations. It consolidates data from all these sources into a unified operational view without requiring system replacement.
Mirage publishes its mining and fleet results per client. At Transwin, five systems run across fuel, mining and fleet, with 12 percent lower diesel consumption across 550 trucks and more than 100 machines, and production reporting that previously required manual consolidation across several systems is generated automatically. Mirage publishes no downtime or fleet-utilization figure: those are measured on your own site during the proof of concept.
The platform is designed for mid-size to large mining operations across metals, minerals, and bulk commodities. It is particularly effective for operations running multiple data systems that do not communicate with each other, sites where equipment downtime is a significant cost driver, and exploration programs where drilling costs justify better target prioritization.
Mining Operations integrates into your existing technical environment without requiring system replacement. Access permissions, validation workflows, and audit trails remain fully controlled by your organization. Every prediction, recommendation, and operational alert generated by the platform is traceable and can be reviewed at any time.
Mirage will map the workflow, identify what can be automated and define the fastest path to production.
Tell us where your team loses time. We send back which workflows are worth automating, what a deployment involves on your systems and the shortest path to production. No commitment.
30 minutes with a Mirage engineer.
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