In a time when AI models are evolving faster than enterprises can adapt, Abhinav Puri, General Manager of Portfolio Solutions & Services at SUSE, believes the answer lies in going back to basics: open-source principles, modular architecture, and long-term infrastructure thinking.
In a recent interview with Geekflare, Puri offered a perspective on how SUSE is helping businesses keep pace with AI without getting trapped in vendor lock-in or proprietary ecosystems.
Open Source Isn’t Just a Philosophy, It’s a Strategy
For companies eager to leverage generative AI, one of the biggest risks is tying themselves to a single vendor. According to Puri, SUSE’s open-source-first approach is designed to counter exactly that.
“Open ways of development accelerate innovation and reduce entry barriers,” he explained. SUSE’s infrastructure platform allows customers to plug in different AI tools and models without having to overhaul their systems. The goal is to give enterprises the flexibility to experiment, iterate, and scale while retaining full control.
He emphasized that this is not just a technical issue. “It’s about the future of AI,” he said. “True open source supports collaborative innovation, and that’s the ecosystem SUSE wants to foster.”
Deploying Models Like Mistral and DeepSeek at Scale
Open-source AI models like DeepSeek and Mistral are gaining popularity, but many organizations still hesitate to deploy them in production environments. Puri acknowledged this gap and positioned SUSE as a bridge.
“Running open models at scale isn’t just about spinning up a container,” he said. It’s about securing the full lifecycle, from training and fine-tuning to deployment and monitoring. Through upstream collaboration and tools like Rancher and SUSE AI, the company is building enterprise-grade solutions grounded in the open-source community.
The focus, he said, is not just experimentation; it’s production-readiness.
Closing the Gap Between Proprietary and Open-Source AI Stacks
Puri didn’t deny that proprietary AI solutions often come with performance and support advantages. But he pointed out that mature open-source tools have come a long way in closing that gap.
With Rancher handling multi-cluster Kubernetes management and SUSE Security (formerly NeuVector) offering runtime protection and deep network inspection, “the trade-off is no longer technical, it’s strategic,” he noted. “It’s about whether you want to own your AI future or rent it.”
Building for What Comes Next
Looking three years ahead in AI is tricky, but Puri believes the answer lies in architecture, not hype.
“Treat every component in your pipeline as replaceable,” he advised. Enterprises should separate the model, data, and infrastructure layers and adopt containerized, security-first workflows. Tools like Rancher and SUSE Security are built with this principle in mind.
AI at the Edge: More Than Just a Trend
As AI moves closer to the edge, powering smart factories, autonomous systems, and real-time analytics, SUSE is adapting its stack accordingly. Lightweight Kubernetes clusters, zero-trust security even in low-bandwidth environments, and enhanced observability through OpenTelemetry are all part of this edge-native push.
“AI is no longer confined to the data center,” Puri said. “It’s becoming distributed, autonomous, and immediate, and we’re building for that reality.”
The New Narrative Around Open Source
According to Puri, one important shift over the past two years is how enterprises discuss open source. “It’s no longer just a cost-saving move,” he said. With AI at the forefront, open source is increasingly viewed as a path to strategic control and innovation velocity.
Puri also pointed out that many organizations are still unsure how to standardize AI practices. SUSE aims to offer clarity here, showing customers which tools can help them adopt generative AI without losing choice or transparency.
So, at the end of the day, one thing is clear: SUSE isn’t about chasing the flashiest models. It’s about helping enterprises stay adaptable as AI continues to evolve without giving up control. And in a landscape that’s shifting by the month, that stability might be the edge businesses need most.
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