More assets, more data, more models, more alarms — across OT, IT, and engineering systems that were never built to act as one.
AGENTIC OPERATIONS FOR INDUSTRIAL ENTERPRISES
Run complex industrial operations better.
XMPro helps industrial enterprises move from operational signals to trusted context, governed decisions, bounded action, and reviewable evidence.
We help industry run the physical world with intelligence that never stops improving.
Monitor. Predict. Advise. Coordinate. Act. Evidence at every step.
THE OPERATING REALITY
The pressure on industrial operations keeps rising.
Industrial operations now depend on thousands of assets, systems, models, alarms, workflows, and human decisions that were never designed as one decision system.
Experienced operators and engineers are retiring faster than they can be replaced, and their judgement is rarely captured.
Teams must still protect uptime, safety, throughput, quality, energy, and cost — with thinner teams and tighter response windows.
The response can’t be another disconnected dashboard or AI pilot. The operation needs a better way to make, govern, coordinate, and learn from decisions.
THE OPERATING CHOICE
Use AI to operate better — not just make work easier.
AI can reduce friction in parts of the work. That helps. But the larger opportunity is to improve how the operation makes decisions, coordinates response, governs authority, captures knowledge, and scales learning over time.
The first use case can be narrow. The operating architecture should be strong enough to scale.
Make work easier
- Copilots & templates
- Dashboards & local productivity
- Short-lived pilots
- Help for individual tasks
Operate better
- Trusted operational context
- Governed recommendations
- Coordinated action & bounded authority
- Reviewable evidence that scales
THE GOVERNED OPERATING PATH
The bottleneck is decision flow.
Industrial teams don’t need another disconnected AI answer. They need the path from signal to action to be visible, governed, and repeatable.
From signal to evidence — visible, governed, and repeatable.
What does XMPro mean for your role?
Keep reading for the strategic-operator narrative, or pick the role that fits you to see the most tailored view and next step.
Start with the future operating model.
Sequence the journey by value, readiness, risk, and evidence.
XMPro isn’t only a full-autonomy story. The same platform supports visibility, prediction, advice, coordination, simulation, human approval, bounded execution, and Decision Trace. The question is where better decisions need more authority — and what evidence earns it.
FOR OPERATIONS LEADERS
Monitor site performance, coordinate cross-functional decisions, and expand bounded autonomy where the evidence supports it.
FOR PLANT & CONTROL ROOM TEAMS
Monitor and predict drift, advise and coordinate response, execute approved routine actions with escalation and Decision Trace.
FOR RELIABILITY & MAINTENANCE TEAMS
Detect degradation, predict failure risk, coordinate maintenance and operations, and trigger governed action paths.
FOR DIGITAL, DATA & AI TEAMS
Build reusable decision patterns on Data Stream Designer, OCE, AI Workflow Harness, MAGS, XMPro FRS, AppDesigner, Action Agents, and Decision Trace.
FOR PARTNER SOLUTIONS TEAMS
Define the customer decision bottleneck, build a reusable solution pattern, and take it to production with XMForge and XMPro platform layers.
VISIBILITY
Monitor & Predict
The platform observes live operational data, surfaces what changed, and predicts where attention is needed. People make the decisions and take the actions.
AgentHuman
Agent Role
Observe & Predict
Human Role
Decide & Act
Target Outcome
Visibility & early warning
Example Capabilities
Real-time operational dashboards
Condition monitoring & alerting
Failure & anomaly prediction
The operating layers of governed decision architecture.
XMPro connects live operational data, trusted context, human workflows, AI-assisted decisions, simulation, bounded action, and Decision Trace in one production architecture.
01
Data Stream Designer
Observe, normalise, enrich, and prepare operational signals.
02
Operational Context Engine
Turn operational data into trusted semantic context and an open, governed ontology. OIM sits inside OCE.
03
AI Workflow Harness
Add governed model reasoning, classification, summarisation, enrichment, structured outputs, and approved tool calls inside visible Data Stream workflows.
04
MAGS
Power AI Assistants, AI Advisors, and Cognitive Decision Teams through governed Cognitive Decision Loops.
05
AppDesigner
Deliver dashboards, workflows, operational applications, and role-based experiences.
06
XMPro FRS
Front-run scenarios against validated domain models before production action.
07
Action Agents + Decision Trace
Route approvals, bounded actions, escalation, human review, and auditable evidence.
Different roles. Same governed path.
XMPro gives operators, engineers, digital teams, partners, and leaders a shared decision architecture, while allowing each role to work at the level of agency and authority that fits the operating risk.
Process Operators
Detect drift, understand consequence, coordinate response, and execute routine actions only where boundaries are approved.
Reliability Teams
Link degradation, causality, failure risk, intervention planning, and production trade-offs.
Operations Leaders
Improve decision quality, knowledge capture, response discipline, and evidence across sites.
Digital & Engineering Teams
Build reusable decision patterns on a governed platform without hard-coding operating IP into one-off tools.
Partners
Package domain expertise into repeatable decision paths, FRS Domain Packs, integration assets, and managed services.
Don’t see your role?
Tell us how your team makes operating decisions — we’ll map the path that fits.
WHY XMPRO
Reasoning models improve inference. Industrial operations need decision architecture.
XMPro is built for safety-critical, asset-intensive environments where decisions affect uptime, throughput, safety, quality, energy, and production commitments.
The outcome isn’t a clever chatbot or a generic agent workflow. It’s governed operational decision flow: trusted context, visible workflows, AI Workflow Harness controls, MAGS-powered decision loops, human review, simulation, bounded action, and evidence.
The whole journey
From visibility to prediction, advice, coordination, simulation, bounded action, and evidence — on one platform.
Trusted, reusable context
Trusted operational context and a governed ontology that make decision logic reusable and scalable.
Authority you earn
Decision architecture that lets authority increase only where evidence and boundaries support it.
Evidence on the record
Decision Trace preserves what was observed, what context was used, which objectives applied, who approved or acted, and what outcome followed.
PROVE IT
Evidence earns authority.
Industrial AI can’t scale on confidence alone. It needs reviewable decisions, explicit boundaries, human control where required, front-running simulation for higher-risk paths, and evidence that can be inspected after the fact.
XMPro helps autonomy earn more authority over time.
EVERY DECISION, ON THE RECORD
An illustrative record — every governed decision is captured the same way, from signal to outcome.
Decision Trace · DR-3017AUDIT TRAILCAPTURED · 2026-05-12 14:32:01 UTC
01Observed14:32:01
Vibration envelope spike on Pump P-301 drive bearing.
source: historian · tag VIB_P301_X
02Reasoned14:32:04
Bearing-wear pattern matched against operating context — degradation trending toward failure.
operational context engine
03Recommended14:32:05
Schedule bearing replacement within the next planned maintenance window.
policy: human-approved · within bounds
04Approved14:36:22
Reliability lead reviewed the recommendation and approved it.
approver: reliability lead · human-in-the-loop
05Executed14:36:40
Work order dispatched to the maintenance system.
action agent · work order created
06Outcome+1 shift
Bearing replaced in the planned window. Unplanned downtime avoided.
recorded to Decision Trace
INDEPENDENT ANALYST RECOGNITION
0+
0
0+
+0%
Industrial AI Market Landscape
Key Vendor
Emerging Tech: Tech Innovators in Agentic AI
Tech Innovator
Emerging Tech: Where Generative AI Works, Will Soon Work, May Never Work
Case StudyPRODUCTION PROOF
In production, not in theory.
BOUNDED AUTONOMY
Autonomy you can measure.
Where authority has been earned, MAGS sustains governed, bounded autonomous operations — with every decision measured, bounded, and on the record.
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
WHAT NEXT
Start with a priority decision path.
The best starting point isn’t a generic AI pilot. It’s a decision path where better context, faster coordination, governed authority, and evidence create operating advantage.
Define the target operating path. Select the first production decision path. Build enough context, governance, and evidence to scale.
GOVERNED . SECURE . PURPOSE-BUILT FOR INDUSTRIAL OPERATIONS