Services · AI Training & Agents
Put AI to work in your engineering team
Training, agent creation and custom skills for engineering workflows — delivered by automation engineers who run their own practice on these tools every day.
What we offer
From first prompt to production agents
Most AI training is generic. Ours is taught by engineers who use these tools on live industrial projects — the examples are PLCs, drives and commissioning logs, not marketing copy.
Hands-on AI training for engineers
From useful prompting to fully agentic workflows — taught on your real plant use-cases, not toy demos. Your engineers leave with working setups, not slideware.
Agent creation
Autonomous helpers for the repetitive engineering work nobody enjoys: code review, documentation, data crunching, report generation — built, tested and handed over.
Custom skills & MCP servers
Connect AI to the tools you already use. We built an MCP server that drives TIA Portal — exporting and importing blocks, compiling projects, reading diagnostics — and we can do the same for your toolchain.
Workflow integration
Memory, hooks, CI pipelines, knowledge bases — AI wired into how your team already works, so it keeps getting used after the workshop ends.
Plant wiki & RAG
Your manuals become a knowledge base the AI actually cites
Every plant has the same library: OEM manuals nobody opens, electrical drawings in five revisions, and PLC programs whose comments are the only documentation that's true. We teach your team to turn that pile into a linked knowledge wiki — and wire it to the LLM with retrieval-augmented generation (RAG).
The difference is trust: instead of a model guessing from training data, it answers from your documents and shows the source — page, drawing number, code block. All of it on-prem, inside your security boundary, and maintained by your own people after we leave.
Hands-on SCL with a coding harness
Working SCL from one prompt — because the rules live in the harness
Ask a bare chatbot for SCL and you get code that looks right and fails in TIA: wrong encoding, timers buried inside CASE branches, naming that matches nobody's library. The fix isn't better prompting — it's a harness where the domain rules are encoded once, as skills, and enforced on every generation.
In the hands-on sessions your engineers build that harness for your own library: UTF-8 BOM handling, stateful-call rules, your block headers and naming conventions. Then they watch one prompt come back as a block that compiles and imports clean, first pass — repeatably, on their machines, after we're gone.
We run our own engineering practice on these tools daily — agents review our SCL, our wiki writes itself from session logs, and our MCP server talks straight to TIA Portal. This is not theory.
How it runs
Four steps, no lock-in
Audit
Half a day with your team to find the workflows where AI actually pays — and the ones where it doesn’t.
Build
We set up the agents, skills and integrations on your machines, with your data, inside your security boundary.
Train
Hands-on sessions where your engineers drive — until the tools are theirs, not ours.
Support
Follow-up as the workflows bed in, plus updates as the AI tooling landscape moves.
Your team, with superpowers
Tell us what your engineers spend their week on — we'll show you which parts an agent should be doing by Friday.
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