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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+

REFERENCE ARCHITECTURE

Reference architecture for governed agentic operations.

XMPro provides the industrial operating layer for AI agents, applications, recommendations, workflows, and governed autonomous operations. This reference architecture shows how that operating layer connects operational data, enterprise context, applications, agents, governance, and decision accountability into one deployable architecture.

AT A GLANCE

One governed foundation for people, applications, and agents.

The XMPro Agentic Operations Platform sits between operational systems and operational action. It connects data sources, contextualises the operation, governs decisions, and serves both human applications and MAGS-powered agents from the same operating foundation.

XMPRO ARCHITECTURE — SIX AREASCLICK TO EXPAND
CROSS-CUTTINGGovernance & decision accountabilityAcross all layers▾
AREA 04MAGS-powered agent layer▾
AREA 03Application & workflow layer▾
AREA 02Operational knowledge foundation▾
AREA 01Data access & contextualisation▾
CROSS-CUTTINGDeployment & operationsAcross all layers▾
Dashed bands are cross-cutting concerns. Solid rows are stack layers.

CORE ARCHITECTURE FLOW

Seven layers of one governed decision architecture.

XMPro connects operational systems, Data Stream Designer, Operational Context Engine, AI Workflow Harness, MAGS, AppDesigner, XMPro FRS, Action Agents, human review, and Decision Trace into one governed decision architecture.

  1. 01

    Operational Systems

    Historians, DCS, SCADA, CMMS, ERP, engineering systems, alarms, work orders, models, and external data remain source systems. XMPro sits above and across these systems to create governed decision flow.

  2. 02

    Data Stream Designer

    Observes, normalises, enriches, and prepares operational signals so they are fit for applications, context, models, workflows, advisors, and decision loops.

  3. 03

    Operational Context Engine

    Turns operational data into trusted semantic context and an open, governed ontology. OIM sits inside OCE as the identity and ontology model. Connects identity, semantics, relationships, constraints, source priority, and lineage.

  4. 04

    AI Workflow Harness

    Governs model reasoning inside visible Data Stream workflows: context assembly, classification, summarisation, enrichment, structured outputs, approved tool access, validation, routing, observability, and governance.

  5. 05

    XMPro MAGS

    Powers AI Assistants, AI Advisors, and Cognitive Decision Teams through governed Cognitive Decision Loops. Uses trusted context to support observation, reflection, planning, coordination, approval, action intent, and Decision Trace.

  6. 06

    Operational Experience and Action

    AppDesigner delivers dashboards, workflows, operational applications, and role-based experiences. XMPro FRS front-runs scenarios, what-if branches, constraints, and proposed action intent before production action. Action Agents execute only through configured pathways. Human review and approval remain part of the architecture where risk demands it.

  7. 07

    Decision Trace

    Preserves the evidence of what was observed, what context was used, which objectives and constraints applied, what recommendation or action was produced, who approved, simulated, escalated, or executed it, and what outcome followed.

Reasoning models improve inference. XMPro provides the operational context, governed workflows, front-running simulation, decision architecture, bounded action, and evidence layer required for industrial operations.

CAPABILITY MAP

The same platform pillars, focused on industrial action.

XMPRO CAPABILITY COVERAGE 8 AREAS · 4 DOMAINS

Foundation

Operational data foundation

Connects operational, enterprise, event, document, and application context into an agent-ready operating foundation.

Real-world operating model

Operational Knowledge Graph models assets, sensors, processes, relationships, policies, enterprise context, identity, trust, and provenance.

Application

Application & workflow layer

Supports operational applications, recommendations, workflows, approvals, and decision review experiences.

AI & agent layer

Gives MAGS-powered agents governed access to operational context, recommendations, and decision pathways.

Governance

Governance & control

Evaluates actions through risk, safety locks, source confidence, policies, approvals, evidence packs, and audit records.

Decision accountability

Decision Trace records what was recommended or done, why, what evidence was used, who or what approved it, and what outcome followed.

Reach

Integration & deployment

Designed for brownfield industrial systems, edge/local patterns, enterprise integration, and cross-site scaling.

Portability & standards

Uses open semantic, validation, query, provenance, and industrial standards where appropriate to avoid trapping operational knowledge in a closed model.

XMPro is not only an application layer on top of someone else’s operating model. It provides the operating model, context layer, application layer, agent layer, governance layer, and decision accountability layer required for agentic operations.

CORE OPERATING MODEL

From data to governed action.

The platform is organised around a simple operating loop. The same five steps run whether a human, an agent, or a policy-controlled action does the work.

01 DETECT

Connect & sense

Connect to live operational data, events, alerts, and context from industrial and enterprise systems.

→
02 DECIDE

Reason & recommend

Use operational context, policies, recommendations, and MAGS-powered reasoning to determine what should happen next.

→
03 COORDINATE

Route & approve

Route decisions through workflows, approvals, applications, and human or agent teams.

→
04 EXECUTE

Act within bounds

Support governed action within human-controlled, human-approved, or policy-controlled boundaries.

→
05 LEARN

Capture & improve

Capture outcomes, evidence, approvals, assumptions, and decision provenance so the operating model improves over time.

The architecture is grounded in action, not just data readiness. It exists to help industrial organisations operate better — not to build a more elegant data model.

DECISION FLOW

Every agentic action follows a governed path.

Eight stops between observation and recorded outcome.

AGENTIC DECISION PATHSTEP 01 / 08
STEP 01

Observe

Agent or application receives operational context.

STEP 02

Interpret

Asset, process, identity, and enterprise context resolved.

STEP 03

Recommend

A recommendation or action is proposed.

STEP 04

Govern

Risk, policy, source confidence, safety locks, approvals checked.

STEP 08

Learn

Outcomes and feedback improve future recommendations and operating context.

STEP 07

Record

Decision Trace captures what happened, why, who approved, and what evidence supports it.

STEP 06

Act

The approved action is executed or handed off.

STEP 05

Coordinate

Decision routes to a human, workflow, agent team, or policy execution path.

CONTROL MODES

Human-Controlled

Agents recommend. A human decides, plans, and acts.

AGENT AUTONOMY
20%

Human-Approved

Agents prepare and coordinate. A human approves execution.

AGENT AUTONOMY
60%

Policy-Controlled

Agents execute within governed policy limits and escalate exceptions.

AGENT AUTONOMY
90%

DATA, CONTEXT & INTEGRATION

Connect existing systems without forcing a full replacement.

XMPro is designed for brownfield industrial environments where critical context is spread across many systems.

  • OT & IT data sources
  • Live operational streams
  • Event & alert data
  • Enterprise records
  • Documents & procedures
  • Operational applications
  • AI-accessible context

XMPro doesn’t require every system to become the system of record. It creates an operating foundation that can connect, contextualise, govern, and act across the systems customers already run.

GOVERNANCE IN THE ARCHITECTURE

Designed for controlled operation, not unmanaged AI action.

Governance is part of the architecture — not a bolt-on control layer.

Human & specialist overrides

Policy-controlled action boundaries

Approval routing

Evidence packs

Decision provenance

Data lineage

Security & access controls

Audit & compliance reporting

The platform earns the right to support autonomy by making decisions governable, explainable, and reviewable.

DEPLOYMENT PATTERNS

Patterns for industrial environments.

Four supported patterns. Pick against connectivity, sovereignty, latency, and governance — deeper detail on the dedicated page.

Cloud

Enterprise-scale analytics, governance, application access, and centralised coordination.

Edge / Local

Site-local context, constrained connectivity, low-latency needs, operational continuity.

Hybrid

Central governance with site-level execution.

Customer-Controlled

Regulated, air-gapped, or sovereignty-sensitive environments.

OPEN STANDARDS

Operational knowledge as a durable enterprise asset.

Open standards for semantic modelling, validation, query, provenance, industrial taxonomies, and AI access — so operational knowledge doesn’t become a proprietary dead end.

OWL 2

Web Ontology Language — semantic modelling.

SHACL

Validation rules for the operating model.

SPARQL

Cross-domain query across the knowledge graph.

PROV-O

Provenance and decision lineage.

MCP

Model Context Protocol — agent-accessible context.

ISO 14224

Industrial reliability and maintenance taxonomy.

ISA-95

Enterprise–control system integration model.

OPC-UA

Industrial automation interoperability.

TECHNICAL PROOF

Architecture proof for technical evaluators.

Starting points for technical evaluation. Need a downloadable architecture brief, a decision-replay walkthrough, or a worked cross-domain query? Talk to a solution architect.

Live product documentation

Technical reference for installation, deployment, configuration, and component behaviour.

Open

Multi-Agent (MAGS)

XMPro’s public repository for generative AI agents and Multi-Agents — the agent layer in code.

Open

Blueprints & Accelerators

Reference implementations and architecture patterns your team can read, adapt, and reuse.

Open

Helm charts

Kubernetes deployment artefacts — concrete starting point for k8s evaluators and platform teams.

Open

DTDL asset models

Real industry asset modelling — Wind Power Plant & Wind Turbine DTDL models you can inspect.

Open

Take the architecture conversation forward.

Walk through the architecture with a solution architect, see it running, or step into integration, governance, and deployment specifics.