Industrial LLM UAE · On-Prem Knowledge AI
On-prem industrial LLM — plant answers with citations, not public-cloud chat.
RAG over manuals, SOPs, alarm guides and approved plant context on your GPU or container hosts. Operators and maintainers get grounded answers inside your security boundary — advise-only by default, never silent PLC writes.
Plant Knowledge AI
Plant knowledge AI — not ChatGPT on the factory network
Factories lose time when tribal knowledge walks out the door. SAS deploys on-prem industrial LLM assistants that retrieve from approved sources — manuals, SOPs, alarm philosophies, maintenance history and selected tag context — then answer with citations supervisors can verify.
Models host on plant GPU servers or container data centers. Role-based access follows your IT/OT policy. AI safety stays clear: advise first; any action path follows human approval and PLC interlocks. Public-cloud LLMs stay optional only when sovereignty rules allow.
Outcome: faster troubleshooting, cleaner shift handovers and less dependency on a handful of experts — without opening the plant to the public internet.
Capabilities
What the industrial LLM delivers.
Grounded answers for UAE and GCC plants — with compute and security engineered for OT reality.
Document RAG
Index manuals, SOPs, P&ID exports and engineering notes with version control.
Alarm & fault assist
Context for common alarm sequences and recommended checks — not random guesses.
Role-aware UI
Operator, maintenance and engineer views with different source access.
Plant context hooks
Optional historian/tag snippets and work-order links when policy allows.
On-prem inference
Plant GPU or container DC hosting — air-gap friendly architectures available.
Safety boundary
Advise-only by default; actions follow Cybersecurity & AI Safety rules.
Typical stack
Sources → secure index → on-prem LLM → HMI / tablet.
Sources
Manuals, SOPs, alarms
Index
Access-controlled RAG
LLM host
Plant GPU / container
Assist
HMI / web / tablet
Human
Operator decides
- Pilot on one area or asset class before plant-wide rollout.
- Citation-first answers so supervisors can verify recommendations.
- Integrates with the same OT zoning and logging as your other AI systems.
- Arabic/English UI options project-dependent — ask during assessment.
Is this ChatGPT for the factory — or something different?
Different by design. We deploy on-prem industrial LLM / RAG assistants grounded in your manuals, SOPs, alarm guides and approved plant knowledge — not an open internet chatbot. Answers stay inside your security boundary.
What data sources can the industrial LLM use?
Typical sources include equipment manuals, SOPs, P&IDs/exports, alarm philosophies, maintenance history, selected historian/tag context and approved engineering notes — indexed with access control so OT and IT stay aligned.
Can the LLM change setpoints or control machines?
No by default. The assistant advises operators and maintainers. Any action into PLC/SCADA follows your AI safety rules — human approval and existing interlocks. See Cybersecurity & AI Safety for the control path.
Does it require cloud or OpenAI connectivity?
No. Many UAE/GCC plants run fully on-prem on plant GPU servers or container data centers. Cloud models are optional only when your policy allows.
Who benefits first — operators, maintenance or engineers?
Usually maintenance and shift operators for faster troubleshooting, then process engineers for procedure lookup. We size the pilot around the role with the highest downtime or knowledge-loss cost.
Is this like ChatGPT for the factory?
It is an on-prem assistant grounded in your approved plant documents — not a public internet chatbot. Answers stay inside your security boundary by design.
Does the LLM control the PLC?
No — advise-only by default, with human-in-the-loop and PLC interlocks remaining authoritative.
We want a chatbot that answers from our manuals
Purchasers say chatbot or ChatGPT; this page is an on-prem plant knowledge assistant over approved documents — not a public internet bot, and not PLC control.
Continue the stack
LLMs need compute, software delivery and safety boundaries.
Edge & Servers
Plant GPU or container hosts for on-prem RAG.
Software Engineering
HMI / tablet UI and plant context hooks.
Cybersecurity & AI Safety
Advise-only modes, access control and audit logs.
Software portfolio
Embedded and industrial software programmes.
Free AI tools
Readiness checklist before a paid LLM pilot.
Plant assessment
Scope sources, roles and compute with SAS.
Next step
Pilot an on-prem industrial LLM on one asset class.
Share document types, target roles (operator/maintenance/engineer) and compute preferences. We propose a RAG pilot with access control and citation requirements.