Use Cases for IT-Operations with KI

AI is Transforming IT Operations

Artificial intelligence has entered many enterprises first in creative and analytical areas — text generation, data analysis, code assistance. IT operations is now following with a force that is fundamentally changing how IT teams work. The combination of Agentic AI, large language models, and standardized integration protocols such as MCP makes it possible to automate routine tasks in IT operations that previously required mandatory human intervention.

Ollama

Self-Hosting AI Models: Privacy-Compliant AI

Using AI language models via cloud services is quick and straightforward — but it comes with a fundamental problem: data leaves the corporate network. For many use cases — internal documents, customer data, source code, financial data — this is not an acceptable option. Local AI models provide a solution: the model runs on your own infrastructure, and no token leaves your own environment.

LLMs Compared

OpenAI, Mistral, Deepseek and Gemma Compared

Large Language Models (LLMs) are AI models trained on enormous volumes of text that can understand, generate, and process natural language. They form the core of modern AI assistants, automated text systems, and — as described in the article on Agentic AI — autonomous AI agents.

Model Context Protocol

What is the Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is an open standard for communication between AI models and external data sources or tools. Developed and published by Anthropic in November 2024, MCP addresses a fundamental problem of modern AI systems: language models are inherently isolated — they have no knowledge of corporate data, cannot call APIs, and have no access to current information. MCP creates a standardized bridge between the AI model and the outside world.