SUSE has recently expanded its AI platform, introducing new tools aimed at controlling workloads and managing LLM (Large Language Model) usage. Despite launching its SUSE AI in November 2024, the platform currently trails its competitors in the industry.
According to Abhinav Puri, VP and GM of portfolio solutions and services at SUSE, the upgraded platform offers crucial insights into AI workloads, token usage, and GPU performance, along with improved functionalities for developing agentic workflows. It also boasts enhanced security features, including LLM guardrails, supporting SUSE’s vision to be the preferred platform for AI application deployments.
Enterprises often face challenges navigating the ever-evolving array of tools and technologies. SUSE AI aims to simplify this landscape by providing a curated set of the best available tools. Initially, the platform included three key components: Ollama for managing LLM installations and embeddings, the Milvus vector database, and OpenWebUI. With recent updates, additional components like MLflow have been integrated to oversee the complete AI lifecycle. Puri noted that further updates would continue to expand the platform’s capabilities.
In a strategic move, SUSE announced a partnership with Infosys, leveraging its Topaz AI platform that includes services and solutions for developing AI applications. This integration will also incorporate the Infosys Responsible AI toolkit, which is open-source and designed to address issues of AI bias, opacity, and security, fostering a collaborative ecosystem.
While these developments signal progress, SUSE faces a formidable competitive landscape. Red Hat, a significant player in the enterprise Linux market, introduced its RHEL for AI platform in May 2024, which supports agentic orchestration and provides a unified platform for creating multi-agent systems. With Red Hat’s reported annual revenues of $6.5 billion compared to SUSE’s $0.67 billion, the competitive disparity is evident.
Experts, like Andy Thurai from Constellation Research, express skepticism regarding SUSE’s AI platform’s utility for enterprises, particularly since many are already exploring options available through the major cloud providers with which they partner. Without a robust ecosystem, the traction of SUSE’s platform remains uncertain. Thurai articulated that SUSE’s offerings might resonate more with current users of their operating system but may not appeal to those looking to build AI applications.
In summary, while SUSE is making strides to enhance its AI platform, questions linger about its ability to attract enterprise customers in a saturated market filled with established alternatives.
