01 CONTEXT & EXPLANATION
AI Assistants
Answer operational questions using trusted context, not generic memory or disconnected prompts.
TYPICAL JOBS ↑XMPRO MAGS · COGNITIVE DECISION LOOPS
Governed Cognitive Decision Loops for industrial operations.
XMPro MAGS powers AI Assistants, AI Advisors, and Cognitive Decision Teams that use trusted context to observe, reflect, plan, and act through governed workflows.
The goal is not model novelty. The goal is better decisions under operational constraints.
Reasoning models are not decision architectures.
LLM reasoning can improve inference. Industrial operations need more than inference. They need trusted context, objective functions, constraints, review paths, approval boundaries, action permissions, and evidence.
XMPro MAGS governs decision loops so AI-assisted recommendations and actions remain tied to operational context, governance, and traceability.
10% — LLM UTILITY
Text GenerationLanguage UnderstandingReasoning SupportCommunicationKnowledge Processing
90% — BUSINESS PROCESS INTELLIGENCE
Scroll to see how the intelligence layer processes decisions →
Assistants, Advisors, and Cognitive Decision Teams share the same governed foundation.
MAGS is the foundation. Assistants, Advisors, and Cognitive Decision Teams are how that foundation shows up in operational decisions.
02 RECOMMENDATIONS
AI Advisors
Recommend responses, explain trade-offs, route approvals, and keep people in control.
TYPICAL JOBS ↑ 03 COORDINATED DECISIONS
Cognitive Decision Teams
Coordinate specialist reasoning across reliability, operations, planning, safety, and production objectives.
TYPICAL JOBS ↑A team coordinates where a single agent cannot.
Specialist agents share memory, reach consensus, and escalate when uncertain — the foundation MAGS gives Cognitive Decision Teams.
Same foundation. Increasing authority.
XMPro is not only a full-autonomy story. MAGS supports a staged path where authority increases only when the operating boundaries, evidence, and governance discipline support it.
Customers can start with AI Workflow Harness and grow into Assistants, Advisors, and Cognitive Decision Teams without leaving the XMPro operating foundation.
OBSERVE
Monitor & Predict
Connect operational data, detect risk, and understand what is likely to happen next. Real-time data, anomaly detection, and leading indicators of failure across your existing operational systems.
AgentHuman
Agent Role
Detect & Surface
Human Role
Decide & Act
Target Outcome
Operational visibility
Example Capabilities
Real-time operational data
Anomaly detection in context
Leading indicators of risk
Fact-based observations. Governed reflection. Bounded action.
MAGS agents evaluate observations from trusted operational context. Not every observation triggers reflection. Not every reflection creates a plan. Not every plan becomes action.
When action is warranted, plans move through configured review, approval, XMPro FRS front-running simulation, consensus, escalation, or action pathways.
- 01
Observe
MAGS agents evaluate operational signals from trusted context.
- 02
Reflect
Not every observation triggers reflection. Reasoning runs only when it matters.
- 03
Plan
Not every reflection creates a plan. Plans form when warranted.
- 04
Act
Plans move through configured review, approval, XMPro FRS front-running simulation, consensus, escalation, or action pathways.
- 05
Decision Trace
Every step leaves a reviewable record.
What Happens in 60 Seconds
When a crusher bearing starts to fail, here's what happens inside XMPro MAGS — a team of specialised agents collaborates to diagnose, plan, and resolve the issue autonomously.
MAGS — AGENT TEAMALERT
Crusher #3 Maintenance Decision
Vibration 8.2mm/s — coordinating diagnostic response
Who closes the loop depends on risk, readiness, and authority.
MAGS supports Human-Controlled, Human-Approved, and Policy-Controlled operating patterns. Higher-risk decisions stay with people. Routine actions can execute only within configured boundaries, permissions, thresholds, and escalation rules.
MODE 01 20%
Human-Controlled
Agents recommend. A human decides, plans, and acts.
AGENT AUTONOMY
MODE 02 60%
Human-Approved
Agents prepare and coordinate the action path. A human approves execution.
AGENT AUTONOMY
MODE 03 90%
Policy-Controlled
Agents execute within governed policy limits and escalate exceptions.
AGENT AUTONOMY
Every governed decision should leave evidence.
Decision Trace records what was observed, what context was used, which objectives and constraints applied, what recommendation or action was produced, who approved it, simulated it, escalated it, or executed it, and what outcome followed.
DECISION TRACE RECORD SCHEMA · 6 FIELDS
- 01 Observed
- What the platform saw.
- 02 Context
- What context was used at decision time.
- 03 Action
- What was recommended or executed.
- 04 Policy
- What policy applied.
- 05 Approval
- Who or what approved it.
- 06 Outcome
- What outcome followed.
From trusted context to auditable evidence.
MAGS sits between the operational context layer and the layers that route, simulate, and execute action. Every step is governed; every step leaves evidence.
- 01
Operational Context Engine
Trusted operational context — the asset, process, and semantic layer every MAGS decision draws on.
- 02
AI Workflow Harness
Governed AI reasoning inside visible workflows: context assembly, tool access, validation, routing, observability.
- 03
XMPro MAGS
Cognitive Decision Loops powering Assistants, Advisors, and Cognitive Decision Teams.
- 04
Assistants · Advisors · Cognitive Decision Teams
The three patterns MAGS expresses — context, recommendation, coordinated reasoning across operations.
- 05
Human Review · XMPro FRS · Action Agents
Review paths, front-running simulation against validated domain models, and bounded action routes when authority is earned.
- 06
Decision Trace
An auditable record of every observation, context, action, policy, approval, and outcome.
Better decisions under operational constraints. In production.
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
Ready for governed Cognitive Decision Loops in your operations?
Put MAGS to work — Assistants, Advisors, and Cognitive Decision Teams reasoning inside visible, governed workflows.
