Netris Raises $15M Series A for GPU Cluster Network Automation

Netris secures Series A to scale GPU networking platform

Netris, a vendor specializing in network automation for GPU clusters, has closed a $15 million Series A funding round led by Andreessen Horowitz. The investment positions the company to capitalize on surging demand for AI infrastructure as cloud providers race to deploy large-scale GPU environments.

According to Telecompaper, which first reported the funding, Netris will use the capital to strengthen its position in network automation and multi-tenant isolation capabilities specifically designed for GPU clusters. The company serves AI cloud providers navigating what it characterizes as unprecedented infrastructure expansion.

Guido Appenzeller, a partner at Andreessen Horowitz, will join Netris's board of directors as part of the investment.

Addressing GPU cluster networking challenges

Netris focuses on a critical but often overlooked component of AI infrastructure: the networking layer that connects GPU resources. As organizations deploy increasingly large GPU clusters for training and inference workloads, traditional networking approaches struggle with the performance, isolation, and automation requirements these environments demand.

The company's platform addresses multi-tenant isolation, enabling cloud providers to securely partition GPU resources across different customers while maintaining the high-bandwidth, low-latency connectivity AI workloads require. Network automation capabilities reduce the operational complexity of managing these specialized environments at scale.

Growth plans and ecosystem expansion

The Series A proceeds will fund team expansion and partner ecosystem development. As GPU availability remains constrained and expensive, cloud providers are under pressure to maximize utilization and operational efficiency—creating opportunities for infrastructure software that reduces overhead and improves resource management.

The timing aligns with broader investment patterns in AI infrastructure tooling, as venture capital flows toward companies solving operational challenges in the AI stack rather than just model development.

Why it matters

GPU networking represents a significant bottleneck in AI infrastructure. As training runs scale to thousands of GPUs and inference deployments require microsecond-level latency, the network fabric becomes as critical as the compute itself. Netris's focus on automation and multi-tenancy addresses two pain points cloud providers face: operational complexity and the need to serve multiple customers on shared infrastructure. The Andreessen Horowitz backing signals venture confidence that specialized networking tools will capture value as AI infrastructure spending accelerates.

The funding details were first reported by Telecompaper.