Description
Almost all agent training is written for chatbots and back-office tasks. This day is written for plant, energy and infrastructure: agents grounded on live sensor data and engineering documentation, connected to maintenance systems, and constrained so they can never take an unsafe action. It is the workshop that closes the "agentic AI" gap our Digital Twin Readiness Scorecard measures.
What you will leave with
- Connect an agent to live time-series telemetry and query it reliably
- Ground answers on manuals, P&IDs and maintenance history with retrieval
- Turn a prediction into an action — raising a work order automatically
- Design guardrails and approval gates appropriate to safety-critical plant
- Judge honestly where an agent adds value and where it is the wrong tool
Agenda
| Why industrial agents fail: the data and trust problems first | |
| Giving an agent your telemetry — querying time-series without hallucination | |
| Retrieval over technical documentation: manuals, drawings, work history | |
| Connecting to the twin: agents that reason over asset state | |
| Closing the loop — from insight to work order in the CMMS | |
| Guardrails for safety-critical action: allowlists, limits, approvals | |
| Evaluating an industrial agent: what "correct" means here | |
| Capstone: an agent that detects drift and raises the job |
Who it is for
Engineers, reliability and operations leads in manufacturing, energy, utilities and infrastructure who already have sensor data and want it to do something.
Prerequisites
Familiarity with your own plant data. Programming helpful but not essential — worked examples are provided.
Format
- Duration: Full day (09:00–17:00)
- Level: Advanced
- Group size: maximum 10 attendees
- Delivery: live online, or in person by arrangement
Need this for a whole team, or extended to full length on your own systems? We deliver every workshop as a bespoke on-site course too — talk to us.
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