Give every recurring operating decision a specialist AI team.
As industrial systems get more complex and skilled teams do more with less, MAGS gives recurring operating decisions a specialist AI team that monitors context, weighs trade-offs, recommends the next step, and keeps action inside governed boundaries.
Fewer missed signals. Clearer trade-offs. Evidence for every decision.
From changing context to governed action
- 1Signal changes
- 2Team reviews
- 3Trade-offs clear
- 4Next step prepared
- 5Evidence retained
Operations are getting harder to run with human attention alone.
Complex systems, scarce expertise, and leaner teams are changing how industrial decisions need to be supported.
Complex systems
More signals, dependencies, and trade-offs to track.
Lack of skills
Expert judgement is scarce and hard to scale.
More with less
Teams need help prioritising what matters.
MAGS decision team
Better-supported decisions, applied consistently.
MAGS helps preserve expert judgement and apply it consistently across recurring decisions.
One operating decision has several trade-offs.
The right decision often depends on production, quality, reliability, safety, energy, and cost at the same time.
Operating decision
Each specialist view has a role in the same decision.
Production
Can we keep running?
Quality
Are we inside spec?
Reliability
What risk changes?
Safety
Are limits clear?
Energy & cost
Is the trade-off worth it?
Human authority
Who closes the loop?
MAGS gives each specialist view a role in the same decision.
From signal to next step.
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Watch
Monitors trusted operating context.
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Assess
Decides whether the change matters.
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Coordinate
Checks specialist trade-offs.
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Recommend
Prepares the next step.
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Record
Keeps decision evidence.
The team handles the work between a signal changing and a human-ready decision.
Different users get different value.
Operator
Fewer missed changes and clearer next steps.
Engineer
Consistent decision logic and visible evidence.
Operations Manager
Repeatable decisions and better escalation.
Risk Leader
Boundaries, approvals, and audit evidence.
The value is better operating decisions with less manual coordination.
The decision path becomes visible.
Before
Signals sit across dashboards, alarms, reports, and spreadsheets.
People manually assemble the situation.
Trade-offs are discussed across calls and handovers.
Decisions are hard to reconstruct later.
With MAGS
The decision team watches the relevant context.
Specialist agents check their parts of the decision.
The team shows the trade-offs in one decision path.
Decision evidence is retained.
Recovery and energy optimisation.
- 1
Feed changes
Operating context moves.
- 2
Quality margin changes
The current target may be too tight or too loose.
- 3
Agents check trade-offs
Economic, process, separation, and safety views align.
- 4
Next step prepared
Hold, relax, tighten, approve, or escalate.
- 5
Evidence retained
The decision path is reviewable.
The team follows a governed decision loop.
Each agent observes context, checks memory and knowledge, reflects on what matters, plans the next step, and acts only through approved pathways.
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Observe
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Use memory & knowledge
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Reflect
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Plan
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Recommend or act
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Record evidence
ORPA architecture diagram
Final XMPro Generative Agent Memory diagram to be placed here (awaiting Pieter's image). The components below are what it must show.
- Live operating signalsReal-time data
- Asset & process contextDigital twin metadata
- Approved domain knowledgeDomain Knowledge Services
- Procedures & reference contentRAG and SOPs
- Calculations & modelsEngineering & math libraries
- What the agent has seenMemory Stream
- Relevant prior contextRetrieved Memories
- Does this matter?Reflect
- What happens next?Plan
- Human-ready adviceRecommendations
- Governed action pathwayAction Agents
The technical architecture supports the decision team — shown after the value is clear.
You decide who closes the loop.
MAGS supports a maturity path. It does not force a jump to autonomy.
The agent works inside boundaries.
MAGS agent
Recommendation or action intent → decision evidence.
Trusted context
What the agent can use.
Objectives
What it is trying to improve.
Policies
What must stay inside limits.
Approved tools
What it can call.
Action rights
What it may route.
Evidence
What can be reviewed.
Every decision leaves a trail.
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Observed
What changed.
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Reflected
Why it mattered.
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Planned
What options were considered.
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Routed
What pathway was used.
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Recorded
What happened next.
MAGS sits between trusted context and governed action.
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Signals
Data Stream Designer
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Trusted context
OCE
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Decision team
XMPro MAGS
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Governed action
FRS · human review · Action Agents
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Evidence
Decision Trace
Start with one recurring decision.
Pick one decision where better context, clearer trade-offs, governed action, and reviewable evidence would change how your operation responds.
