FIS Group Builds Trusted AI for SAP Clients with SUSE AI

As artificial intelligence transforms enterprise IT, one of Germany’s leading SAP partners demonstrates how open infrastructure can turn AI complexity into a competitive advantage. The FIS Group, an independent IT service provider and SAP Gold Partner, has adopted SUSE AI to develop and operate trusted, scalable AI solutions for SAP environments. Through this partnership, FIS has established a model for delivering secure, high-performance AI in regulated industries while keeping full data sovereignty.

FIS creates intelligent applications for SAP customers in manufacturing, retail, and wholesale industries. Its innovations include automated invoice processing and real-time product recommendations, all powered by AI models trained in its secure data centers. A proprietary embedding model called FISMWASP transforms complex enterprise data into multidimensional vector spaces for faster, more accurate insights.

Why FIS Chose SUSE

For FIS, the decision to adopt SUSE AI was motivated by the need to simplify the deployment and management of various AI workloads. The SUSE AI platform, built on SUSE Rancher Prime, provides a unified layer for orchestrating, monitoring, and managing multiple large language models (LLMs) across different environments. Instead of manually configuring complex infrastructure, FIS can now quickly deploy, scale, and maintain AI models, reducing operational overhead.

According to FIS-ASP Managing Director Manuel Sammeth, “A major advantage of SUSE AI is that it significantly reduces the complexity of operating AI workloads. We can manage different large language models via a central platform and implement new models for our customers very quickly when needed.” The integrated observability tools within SUSE AI were another decisive factor. By providing real-time visibility into model performance, GPU utilization, and token usage, FIS can proactively identify bottlenecks, maintain service-level agreements, and optimize costs.

Security and compliance were also nonnegotiable. Many SAP customers operate in highly regulated industries and are reluctant to use public-cloud AI models due to data privacy laws. SUSE AI’s end-to-end security, backed by SUSE Security and a verified open-source supply chain, ensures that data remains protected throughout the AI lifecycle. Built-in Guardrails AI mechanisms help FIS enforce ethical standards, improve traceability, and ensure alignment of output with user intent.

Extending Trusted AI from Data Center to Edge

The next phase of FIS’s AI strategy emphasizes bringing trusted AI closer to the data sources. By integrating SUSE Edge and SUSE Linux Micro, the company is expanding its AI workloads beyond centralized data centers into local environments like logistics hubs, factories, and retail stores. This enables real-time processing with low latency and greater control over sensitive data.

For SAP clients, the architecture integrates smoothly with SAP Edge Integration Cell, which extends the capabilities of SAP Integration Suite to edge locations. SUSE’s validated technology stack for SAP workloads enables secure deployment and management of these distributed systems. Built on SUSE Rancher Prime and SUSE Linux Micro, the platform provides a lightweight, containerized foundation that ensures consistent performance and simplified operations from data center to edge.

What This Means for SAPinsiders

AI infrastructure for SAP is becoming simpler and more secure. For SAP technology leaders, the FIS case study shows how SUSE AI streamlines complex workloads into a single manageable platform. Its built-in observability, orchestration, and lifecycle management can greatly reduce the friction that often delays AI adoption. CIOs can now deploy trusted AI within SAP systems faster, keeping sensitive data protected while enhancing operational agility.

Observability is essential for operational success. Using tools that monitor token usage, GPU performance, and model activity, SUSE AI helps teams identify inefficiencies and security issues early. FIS’s experience demonstrates that predictive monitoring and unified dashboards can shift from reactive troubleshooting to proactive optimization. In SAP environments, observability ensures AI performance remains transparent, verifiable, and consistent with enterprise SLAs.

Open, vendor-neutral platforms are an attractive way forward. The FIS–SUSE partnership demonstrates a growing preference for open-source, modular systems that avoid vendor lock-in. By choosing SUSE AI, enterprises can access the latest AI tools, adapt quickly to technological changes, and maintain data sovereignty. SAP professionals evaluating AI infrastructure should focus on simplicity, observability, and openness as essential criteria for sustainable innovation.