exemplarisch

Übergabe- und Betriebsdokumentation

Das interne Team befähigen, den KI-Workflow eigenständig zu warten, anzupassen und zu skalieren.

Wenn externe Berater gehen, muss sichergestellt sein, dass das wertvolle Prozess- und Technikwissen im Unternehmen bleibt.

Primary BenefitKnowledge transfer and team enablement

ApplicationProject completion and go-live

OutputOperations manual & SOPs

When this template makes sense

Makes sense when...

External consultants are building an AI system for you and your team should maintain and control it themselves in the future.

RAG solutions, prompt chains, low-code pipelines (Make/Zapier), and custom GPT rollouts across the organization.

A clear operations manual with architecture diagrams, prompt maintenance guidelines, and a compact troubleshooting guide.

At a glance

Use Case	Smooth internal continuation of completed AI solutions
Why important	Secures investments made and avoids long-term dependencies on developers
What is created	Architecture sketch, prompt library rules, troubleshooting
Status	Exemplarily adaptable for low-code automation

Important chapters of the documentation

How does the data flow? Diagram of linked tools (e.g., Email -> Make.com -> OpenAI -> CRM) and permissions.

Where exactly are the system prompts, how can they be adjusted by non-programmers, and why old versions are preserved.

What to do when the token limit is reached, the API fails, or the AI assistant suddenly throws error messages to the team.

Listing of all generated cost centers (LLM providers, RPA tools, cloud hosting) and thresholds for budget alerts.

Checklist for a clean handover

Before an external consultant leaves the project, these organizational points must be clarified:

Source code or automation scenarios are hosted in the customer account (not with the consultant)
All API keys run through official company credit cards to avoid downtimes in case of consultant failure
An internal "AI responsible person" has been technically briefed on the platform
Emergency contact details for support (which bug goes to the consultant, which to the SaaS provider?) are documented

Excerpt: Troubleshooting Guide

Often, customers call the consultant weeks later because small errors occur. A good troubleshooting guide empowers the team for self-help.

Error ImageThe AI suddenly responds in English instead of German

ActionCheck the system prompt in the platform; often the "Language" setting has been overwritten by a UI update.

Error ImageError "Rate Limit Reached" appears in the CRM

ActionThe monthly budget limit at OpenAI/Azure has been reached. Admin must raise the hard limit in the cloud portal.

Error ImageAutomation (Make/Zapier) stops after 50% of the steps

ActionCheck the execution log. The LLM likely output an invalid JSON that caused the error in the next step.

Alle Inhalte sind exemplarisch, anonymisiert und ohne Bezug zu realen Kunden erstellt.

We not only take care of the implementation but also document everything so that your team is in control.