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AI320-WS: Crisis-Resilient AI: Blackout-Capable Knowledge Assistant with Local LLMs and RAG

Web Seminar: Artificial Intelligence

In the web seminar, participants learn to build and use an internal corporate knowledge assistant with local Large Language Models and RAG – privacy-compliant, without cloud dependency, and usable even with limited internet availability or outages of external IT services. In a practical way, it is shown how documents, manuals, processes, and experiential knowledge become easier to find faster, onboarding is shortened, and professionals are relieved in day-to-day work.

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Appointments in German language (1)


Online event	2026-05-18 \| 04:00 pm	2026-05-18 \| 05:00 pm	Online

Possible course languages: German

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Online event

Start: 2026-05-18 | 04:00 pm

End: 2026-05-18 | 05:00 pm

Location: Online

Price: 0,00 € plus VAT.

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Agenda:

Why “crisis-resilient AI”?
- typical disruption scenarios, knowledge bottlenecks, dependencies
Local AI made understandable
- LLMs, on-prem/edge, what does “local” really mean?
The knowledge assistant: LLM + RAG in practice (15 min)
- documents → search/answers → sources/transparency, typical architecture
Use cases for mid-sized companies
- production/service/QM/administration: where the biggest leverage is
Effort, risks & guardrails
- data foundation, access control, quality, operations, pragmatic governance
Approach in 3 steps
- quick check → pilot → rollout (incl. “no-go” criteria)
Q&A

Objectives:

Participants will learn:

what “local AI” means in practical terms – clearly and without technical jargon
how an internal knowledge assistant works (LLM + RAG) and why it does not have to be a “black box”
which use cases are realistic for mid-sized companies (production, administration, service, quality management, sales)
which prerequisites and what level of effort are typically required
which risks (data protection, information quality, access control) should be considered and how to address them pragmatically

The goal is to provide a clear picture of whether – and how – this technology can make economic sense for your company: today, not in five years.

Target audience:

The web seminar AI320-WS Crisis-Resilient AI: Blackout-Capable Knowledge Assistant with Local LLMs and RAG is aimed at:

ML/AI engineers, data scientists (engineering focus)
Software engineers/tech leads with responsibility for LLM integration
MLOps/platform/architecture roles responsible for designing LLM pipelines, deployment, and operations

Prerequisites:

For participation in the web seminar AI320-WS Crisis-Resilient AI: Blackout-Capable Knowledge Assistant with Local LLMs and RAG, the following prerequisites are required:

Basic knowledge of Python
Basic understanding of ML (train/test, overfitting, loss/metrics)

Description:

Cyberattacks, system outages, or limited internet availability show: digital dependencies are becoming a business risk. At the same time, enormous potential lies in company documents, manuals, processes, and experiential knowledge—yet it often remains unused in day-to-day operations.

This web seminar AI320-WS Crisis-Resilient AI: Blackout-Ready Knowledge Assistant with Local LLMs and RAG shows how an internal corporate knowledge assistant based on local AI (Large Language Models) and RAG (Retrieval Augmented Generation) can be used: compliant with data protection requirements, without cloud dependency, and with the option to remain usable even when external IT services are disrupted. Instead of “AI gimmickry,” the focus is a practical approach for small and medium-sized enterprises to make information easier to find, shorten onboarding times, and relieve specialists in their daily work.