Akamas Launches AI Infrastructure Optimization to Improve GPU Efficiency and Reduce AI Costs

NEW YORK, June 9, 2026 - Akamas today announced the launch of AI Infrastructure Optimization, extending its optimization platform to GPU-powered AI workloads running on Kubernetes.

As enterprises move AI initiatives from experimentation into production, infrastructure teams face growing pressure to balance performance, reliability, throughput, and rapidly increasing GPU costs. While observability platforms provide visibility into AI systems, identifying the best configuration across infrastructure, orchestration, and inference-serving layers remains largely a manual and time-consuming process.

Akamas addresses this challenge by extending its optimization technology to AI infrastructure environments, enabling organizations to continuously identify and validate optimal configurations across Kubernetes environments, GPU resources, AI serving infrastructure, and inference runtime parameters.

The new capabilities help organizations improve GPU utilization, increase application throughput, reduce AI operating costs, and balance competing objectives such as performance, reliability, efficiency, and infrastructure spend. Rather than relying on static best practices or manual experimentation, Akamas continuously evaluates thousands of possible configurations to identify the best operating conditions across the AI stack.

Built on the same optimization technology already used to improve the performance and efficiency of enterprise applications, cloud environments, and Kubernetes workloads, the new capabilities enable engineering teams to make data-driven optimization decisions in increasingly complex AI environments.

"Everybody is talking about AI models. Very few people are talking about the operational cost of running them at scale," said Luca Forni, CEO of Akamas. "As organizations move from experimentation to production, optimization becomes just as important as innovation. We've spent years helping enterprises optimize applications, Kubernetes environments, and cloud infrastructure. AI infrastructure is simply the next frontier. The challenge is no longer just building AI systems-it's operating them efficiently, reliably, and economically."

The launch reflects a growing need for technologies that help organizations move beyond visibility and monitoring toward active optimization of AI infrastructure and workloads.

The new AI Infrastructure Optimization capabilities are available immediately as part of the Akamas platform and are being introduced this week at Datadog DASH 2026 in New York, where Akamas is exhibiting at Booth #532.

Akamas SPA, Via Schiaffino 11, 20158 Milano (Italy)

Akamas is anautonomous optimization platform that helps organizations improve performance, reliability, and infrastructure efficiency across Kubernetes, cloud, enterprise applications, and AI workloads.
For more information, visit https://akamas.io

This release was published on openPR.