Simplifying SAP infrastructure operations with an AI companion

Managing SAP infrastructures is a complex and time-consuming task. Even with powerful tools such as Trento, which continuously deliver data—from real-time monitoring to proactive alerts—the workload remains high. Sifting through this information, identifying risks, and determining the right course of action is a slow, manual process. The next step is to reduce this workload and shift from human interpretation to automated AI analysis, allowing experts to focus on strategic outcomes.

AI-supported operational processes

As the discussion surrounding AI continues to grow, companies are looking for practical application scenarios that deliver a clear ROI while also taking data protection into account and controlling costs. This requires a focused approach:

Use AI in a targeted manner to solve specific, business-critical problems. In this context, AI solutions can serve as a helpful multiplier for teams of experts—by providing tools that reduce the daily workload and extract valuable insights from operational data. The key is to have a large language model (LLM) analyze your SAP data—without the security risks and costs of model training.

This is achieved with the Trento MCP Server. It uses the Model Context Protocol (MCP)—a new open standard for secure data exchange with AI—and provides your chosen LLM with live information from Trento's monitoring. This approach enables the LLM to analyze your SAP landscape in real time, eliminating the need to train the model on your private data. Connecting Trento's real-time data to an AI companion transforms operations from simple monitoring to intelligent automation – with several key advantages:

Automated root cause analysis: Instead of just reporting a problem, AI compares alerts with Trento metrics and logs to identify the actual cause. This saves valuable analysis time by providing a clear explanation and recommended actions.

Proactive problem solving: AI helps teams shift from reactive to proactive action. By analyzing data patterns, it identifies potential bottlenecks before they become critical and enables a solution to be found before business processes are affected.

Improved strategic insights: AI generates in-depth insights that might otherwise be overlooked. For example, an administrator might classify a routine cluster alert as non-critical. AI, on the other hand, can link it to a non-compliant configuration in a business-critical database. By connecting these seemingly unrelated data points, AI identifies a hidden operational risk and enables faster, more informed decisions.

The Future of SAP Operations

In an era of rapid LLM innovation, the path forward for managing complex SAP infrastructures is clear: move away from manual analysis of observability data toward automated, AI-powered insights. The key to this transformation lies in leveraging rich real-time data from tools such as Trento to predict problems, automate root cause analysis, and uncover strategic risks. MCP has established itself as the definitive standard that makes this possible in a secure and flexible way. By deploying a Trento MCP server, any LLM can work with your live operational data without the risk and cost of model training. This approach is more than just an operational upgrade; it is a strategic decision to create a future-proof foundation.

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