See It Work
See It Work
SYSTEM: OPERATIONAL OT/IT CONNECTORS: 150+ AUTONOMOUS OPERATION: 15+ DAYS GOVERNED AUTONOMY: ENFORCED AUDIT TRAIL: IMMUTABLE INDUSTRIES: ASSET-INTENSIVE & MISSION-CRITICAL DEPLOYMENT: 3-6 MONTHS VIA APEX CONTROL LOOPS: 3,400+ SYSTEM: OPERATIONAL OT/IT CONNECTORS: 150+ AUTONOMOUS OPERATION: 15+ DAYS GOVERNED AUTONOMY: ENFORCED AUDIT TRAIL: IMMUTABLE INDUSTRIES: ASSET-INTENSIVE & MISSION-CRITICAL DEPLOYMENT: 3-6 MONTHS VIA APEX CONTROL LOOPS: 3,400+

Predictive Quality · PROCESS INDUSTRY · MANUFACTURING

Cheddar that ages the way the spec says it should.

Cheddar production chains milk standardisation, pasteurisation, curd cutting, whey separation and aging — and inconsistency at any stage shows up in the final product. The XMPro AO Platform monitors the full process in real time and uses predictive analytics to keep curd size, moisture and aging on target across every line.

THE CHALLENGE

What's getting in the way today.

Cheddar production has to balance quality, yield and compliance against several compounding pressures:

ISSUE 01 OPEN

Milk-quality variability

Incoming milk fat and protein levels shift by source and season — without continuous control, the variation reaches the curd.

ISSUE 02 OPEN

Curd processing efficiency

Optimal curd size and moisture content drive uniform texture and flavour. Small drifts produce noticeable inconsistency in the wheel.

ISSUE 03 OPEN

Aging-process control

Aging is unforgiving: over-age or under-age and the spec breaks, with no path to recovery.

ISSUE 04 OPEN

Yield and waste

Maximising cheese yield while minimising waste demands tight process control across every line, every shift.

THE SOLUTION

Dairy Process Optimisation — how it works.

A continuous picture of every stage — milk standardisation, curd processing and aging — with predictive analytics surfacing adjustments before product drifts off-spec.

Real-time data integration Predictive analytics Anomaly detection Automated recommendations Operational dashboards Digital twin simulation

The platform integrates live sensor telemetry from existing control systems across pasteurisation, curd cutting, whey separation and aging. A digital twin of the cheddar process lets engineers simulate adjustments against historical batches before changing anything on the line. Predictive analytics models forecast quality and yield against the spec and surface ranked recommendations when conditions begin to drift. Threshold breaches generate alerts routed to the right operator, and configurable dashboards drill from plant-level health into per-batch detail with automated traceability for compliance and customer reporting.

SEE IT IN YOUR ENVIRONMENT

Scope this for your operation.

Tell us about your fleet, your control maturity and the lever that matters most. We’ll map this use case to your starting point.

WHAT CHANGES

What this looks like in operation.

Consistent product to spec

Real-time control narrows the variability that reaches the wheel — texture, flavour and moisture stay on-spec across shifts.

Higher yield, less waste

Per-batch baselines expose the conditions that drive cheese yield, and the conditions that cost it.

Compliance as a by-product

Automated traceability turns regulatory and customer reporting into an output of normal operations rather than a separate exercise.

DEPLOYED IN

Built for these industries.

PRODUCTION-PROVEN

Not a concept. In production.

XMPro is deployed at Tier 1 global operators across asset-intensive and mission-critical industries — delivering measurable results across predictive maintenance, process optimisation and operational intelligence.

VERIFIED RESULT — OIL & GAS
$16M Saved every year
18% Reduction in field service trips
95% Reduction in maintenance planning

Customer Case Study

Using XMPro, a global oil and gas supermajor rapidly composed and deployed an intelligent oil well maintenance solution in just three months -- achieving over $8 million in calculated value within the first six months.

VERIFIED RESULT — MINING
$10M Saved every year
30% Reduction in conveyor downtime
9,000t Saved every month

Customer Case Study

Using XMPro, the world's largest potash mining company rapidly composed and deployed a predictive maintenance solution for over 50 miles of underground conveyors in just 30 days, achieving $10 million in savings every year by reducing unplanned downtime by over 30%.

VERIFIED RESULT — ENTERPRISE SCALE
6 Sites with in-house adoption
1,000+ Assets monitored
35+ Operational, tactical and strategic use cases

Customer Case Study

XMPro enabled the in-house engineering team at a major North American miner to independently compose 35 operational, tactical and strategic solutions across six sites, scaling to monitor and manage over 1,000 diverse critical assets.

"XMPro successfully triggered a real predictive maintenance alert for a Haul Truck that appears to have a Strut issue - This was particularly impressive, considering we have only deployed the development environment a few weeks ago"

-- Advanced Predictive Maintenance Lead, major global mining company

AUTONOMOUS OPERATIONS

Now pushing the frontier.

MAGS agents are achieving what no other industrial platform has demonstrated — sustained autonomous operations at enterprise scale.

0+
Days Autonomous
Safety-critical petrochemical operations
3-0+
Agents Per Team
Specialized agents coordinating per use case
0+
Teams Deployable
Scale across sites and business units
0%
Governed
Every agent, every decision, every action — auditable

SCOPE FOR YOUR SITE

Let’s scope this for your operation.

Talk to an XMPro engineer about your environment, your starting HAS level and the lever that matters most — or browse more solutions.