Workshops

Understand AI and apply it.

Practical workshops for teams that want to bring AI into daily work in a useful, safe and productive way.

What this is about

No generic showcases. We work on your real tasks.

Many AI workshops end with “interesting, but how would this work for us?” Generic examples rarely translate into real work.

We prepare workshops around your documents, processes and questions. In the workshop, people work on invoices, requests, contracts, reports and the tasks waiting tomorrow.

At the end, every participant has a realistic view of AI, concrete use cases and a checklist for safe use.

01

AI fundamentals for teams

What models can do, where their limits are and how prompts, data and processes fit together.

We also cover hallucinations, bias, privacy, copyright and error-proneness without hype.

  • What a language model is and is not
  • Prompt practice with real tasks
  • Strengths and limits of large models
  • GDPR and AI Act in plain language
  • Safe tool selection
  • Exercises with ChatGPT, Claude, Mistral or local models
AI fundamentals for teams
02

Automation workshop

We identify and prototype concrete automations with your team. Day one yields use cases; the end yields a prioritized pilot proposal.

Small groups work with real examples and tools that can be used afterward.

  • Use-case mapping from daily work
  • Rough but realistic ROI estimate per use case
  • Feasibility check: data, interfaces and risk
  • Shared roadmap draft
  • Tools your team can use directly
Automation workshop
03

AI rules for daily work

Teams learn which data may go into AI systems, how results are checked and where approvals are required.

Instead of a long policy nobody reads, we create clear guardrails: yes, no and approval needed.

  • Data classes: public, EU-only, local-only
  • Escalation paths for critical content
  • Labeling duties for AI-generated content
  • Examples from your company
  • One-page checklist for safe daily use
  • Adaptable to healthcare, finance, legal or public sector
AI rules for daily work
04

Leadership compass

A half-day format for management, department heads and supervisory bodies: strategic context, practical impact and decisions to make now.

Content is tailored to your industry, size and competitive situation.

  • Where AI changes your business model
  • What competitors do and what inaction costs
  • Build, buy or wait decisions by domain
  • Compliance, liability and insurance questions
  • A six-point plan for the next 12 months
Leadership compass
05

Technical deep dive

For IT teams, developers and data professionals: RAG, embeddings, vector databases, function calling, evals and security patterns at code level.

We work in a real repository, write tests, build a small RAG system with sources and discuss failure modes honestly.

  • RAG architecture: chunking, retrieval, reranking and eval
  • Function calling, tool use and agent patterns
  • Host models locally where needed
Technical deep dive
Process

A clear path.
A clean handover.

01 · Briefing
Audience & goals
We tailor content to prior knowledge, industry and concrete questions.
30 min.
02 · Preparation
Material & use cases
Examples, exercises and data come from your work context wherever possible. Sensitive data can be anonymized.
1 week
03 · Workshop
Practice before theory
Short inputs, lots of trying, clear guardrails. Half-day, full-day, on site, hybrid or online.
half day to 2 days
04 · Transfer
Roadmap & follow-up
At the end you receive use cases, recommendations and a checklist. Optional follow-up office hours are available.
document + follow-up
Frequently asked questions

Concrete questions.
Concrete answers.

Is the workshop technical or business-focused?
Both are possible. For business teams we explain AI practically; for technical teams we go deeper into data, models, evals and integration.
Do we work with real tasks?
Yes. The workshop is better when real documents, processes or questions are brought in. Sensitive data can be anonymized beforehand.
What happens after the workshop?
You receive concrete use cases, value and risk estimates, and suggestions for pilots or internal rules. Optional follow-up support is available.
Online, on site or hybrid?
All are possible. On site works best for workshop formats, online is efficient for knowledge transfer, hybrid works for distributed teams.
Which languages?
German and English at comparable quality. Modules can also be mixed if needed.
Which tools do we use?
Depending on format: ChatGPT, Claude, Mistral, local models, Microsoft Copilot or Google Workspace AI. We recommend what fits your data situation.
Contact

Good to see you here.

Tell us what you are working through. We reply within 24 hours with a proposal for a conversation. No sales routine. No questionnaire.