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AI that actually helps in engineering.

Modern language models — Claude, ChatGPT and similar — have long moved past novelty. Used properly, they save engineering teams hours each week: structuring reports, sifting through logs, translating specifications and getting up to speed on unfamiliar systems. egatti engineering takes a pragmatic, realistic approach — without the hype.

Claude ChatGPT Prompt engineering MCP / agents GDPR-aware

What we don't do

We don't sell black boxes, and we don't promise „AI that automates everything“. Instead:

  • We show which questions AI answers well — and which it doesn't.
  • We build prompts your team can reuse.
  • We review with you where trade secrets or GxP set a hard boundary.

Concrete use cases

Documentation & reports

Commissioning protocols, deviation reports, technical descriptions and user requirements — drafted more structured and faster.

Log & trend analysis

AI-assisted first pass on fault data, trends and audit logs — with the engineer validating the result.

Multilingual technical writing

Specifications, emails and instructions between DE, EN and FR — with domain vocabulary, not Google-Translate boilerplate.

Troubleshooting co-pilot

A second pair of eyes on tricky faults — with hypotheses, a checklist of questions, and plain-language explanations.

Prompt libraries

Reusable, reviewed prompts for automation, electrical, QA and project teams — available to the whole team.

AI agents & MCP

Small, controllable agents that connect file stores, logs and measurement databases — via the Model Context Protocol.

How a typical AI introduction project runs.

Start small, learn, roll out. No monster rollouts, no tool stacks that end up in a drawer.

  1. 01

    Workshop & use-case screening

    We identify 2-3 concrete tasks where AI can help today — and, equally important, where it can't.

  2. 02

    Privacy & rights check

    GDPR, trade secrets, GxP — what data is allowed with which model? Output: clear guardrails.

  3. 03

    Pilot with real data

    One department, one use-case, four to six weeks. We coach, measure time saved and output quality.

  4. 04

    Training & prompt library

    The team gets reusable prompts, a short training session and a lean governance document.

  5. 05

    Rollout & review

    Step-by-step rollout to further teams, a six-monthly review — including model versions and privacy updates.

Privacy & trade secrets first.

We pick the model deployment that matches your sensitivity: EU region, enterprise access without training use, or locally hosted models for particularly sensitive data. No AI project begins without clarity on which data is allowed to go where.

Typical guardrails

  • · No customer names in consumer chat UIs
  • · No recipes or SIL documents in consumer tools
  • · Disable training use, prefer enterprise access
  • · Validation: engineer decides, AI assists

Ready for a pragmatic AI pilot?

A short conversation is enough to figure out where a pilot makes sense — and where it doesn't.