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Governed Industrial AI
Your AI Agent Needs a Harness
Bring model reasoning, classification, enrichment, structured outputs, and approved tool calls into the industrial workflows you already run.
- Existing systems
- Governed harness
- Trusted decision
Generic agents were not built for the plant.
Industrial operations run across historians, SCADA, PLCs, MES, EAM, ERP, lab systems, edge devices, procedures, and change-control requirements. A generic prompt-and-tool chain is not enough for production decisions.
Systems of record & control
- Historian
- SCADA
- PLCs
- MES
- EAM
- ERP
- LIMS
- Edge
The model is one part of the system. What it sees, does, validates, and records is governed by everything around it.
The model reasons. The harness governs everything else.
An industrial agent needs a visible workflow layer around the model — six governed stages that control what it receives, what it can do, how outputs are checked, where decisions go, and what is recorded.
- 01
Data ingress
Pull live signals from historians, SCADA, MES, ERP, lab systems, and edge.
- 02
Context assembly
Assemble trusted operational context, identity, and lineage.
- 03
AI reasoning
The model classifies, summarises, enriches, or structures the content.
The model - 04
Output guardrails
Validate outputs against required format, confidence, and policy.
- 05
Action routing
Route results to people, workflows, systems, or MAGS.
- 06
Observability & audit
Capture what was used, produced, approved, and actioned.
Governed by the harness The model
AI Flow puts model reasoning inside visible Data Stream workflows.
XMPro AI Flow is the practical entry point: governed model use inside the workflows you already run, before your organisation commits to full cognitive autonomy.
Explore AI Flow- Assemble trusted operational context.
- Call approved tools and Data Streams.
- Validate structured outputs.
- Route recommendations to people, workflows, systems, or MAGS.
- Preserve evidence for review.
Add governed AI to the operation — don’t replace it.
-
Keep the systems you already run
No rip-and-replace. AI reasons across your historians, SCADA, MES, EAM, ERP, and lab systems in place, and your systems of record stay the source of truth.
-
Trust what the agent recommends
Every recommendation arrives context-grounded, validated, and routed to the right review, with an audit trail behind it instead of a black box.
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Earn autonomy at your pace
Prove the value on one governed workflow, then extend toward MAGS cognitive decision loops when the use case and governance are ready.
MAP ONE GOVERNED AI WORKFLOW
Start with one operational decision.
Pick one operational decision. Identify the triggering event, required context, AI role, validation rules, review path, allowed system actions, and audit requirements.
- What event starts the workflow?
- What context is needed?
- What should AI reason over?
- What validation rules apply?
- Who reviews the recommendation?
- What system action is allowed?
- What should be audited?
READY WHEN YOU ARE
Book a workflow scoping session
We’ll map the event, context, AI role, validation, review path, allowed actions, and audit trail for one workflow — and where AI Flow fits.
Book a workflow scoping sessionMore on governed industrial AI.
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INDEPENDENT ANALYST RECOGNITION
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TAKE THE FIRST STEP
Map one governed AI workflow.
Pick one operational decision. We’ll map the event, context, AI role, validation, review path, allowed actions, and audit trail, and show where AI Flow fits.
Book a workflow scoping session