The bridge between enterprise AI and the edge

In the rapidly evolving technology landscape of 2026, AI for businesses has grown far beyond simple public cloud integrations. Organizations are increasingly adopting a „Bring Your Own Model“ strategy to maintain control over sensitive data and customized large language models. Two dominant architectural patterns have emerged for secure workload operations: Agents communicating with cloud-based SAP BTP via Suse AI, and deploying Suse AI in your own data center with the SAP Edge Integration Cell (EIC).

Cloud strategy: Suse AI and SAP BTP

For many companies, Suse AI acts as a secure, private „factory“ where infrastructure teams build, train and fine-tune open source models - such as Llama 3 or Mistral - based on proprietary company data. A reliable „delivery vehicle“ is required to integrate the model into daily business processes. BTP takes on this role. The workflow for connecting the two environments is standardized: First, the fine-tuned model is packaged into a container.This container is then registered and uploaded to SAP AI Core - a specialized component of BTP designed for custom AI workloads. The main benefit of transferring a private model from Suse AI to BTP is the gain in business context. This allows customers to use custom LLM as an intelligent backend for no-code applications in SAP Build or as specialized „skills“ for SAP Joule to answer highly specific business questions.

Edge strategy: Suse AI and SAP EIC

While the cloud offers seamless S/4 Hana integration, the use of Suse AI together with SAP EIC is arguably the most powerful architecture available to an organization in 2026. This combination enables a complete „private AI“ loop where the data, LLM and integration logic remain securely and completely within the corporate firewall.

In this setup, the tasks are strategically separated: when designing in the cloud, integration flows (iFlows) are modeled within the SAP Integration Suite. When executed at the edge, the actual execution takes place locally. The iFlow is provided on the Edge Integration Cell, which runs on Suse Rancher for SAP applications. This is also where the private LLM is located directly next to the SAP data. 

When the EIC executes its logic, the API calls to the LLM are made locally on Suse AI, ensuring that no data leaves the network.

Ground-to-ground

This local „ground-to-ground“ AI pattern offers enormous advantages for companies that use on-premises systems such as SAP ECC or S/4 Hana. As there are no detours via the internet to a cloud LLM, the latency drops from seconds to a few milliseconds - a basic requirement for real-time production and high-volume logistics.

In addition, this edge architecture guarantees absolute data sovereignty. Strictly regulated sectors such as banking, healthcare and defense are subject to strict data residency laws that prohibit sensitive data records from passing through the public Internet. Since both the EIC and Suse AI are operated entirely in the private data center, they easily meet these compliance requirements. The system also offers unrivaled offline resilience: EIC supports up to four hours of offline operation. If the internet connection in a data center fails, the critical AI-supported processes continue to run seamlessly.

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