Netris Raises $15M Series A Led by Andreessen Horowitz to Scale AI Networking

Netris, a Santa Clara, California-based software company building network automation for AI infrastructure operators, announced a $15M Series A led by Andreessen Horowitz. The round supports team expansion, broader hardware support, continued platform development, global growth, and expansion of the company's partner ecosystem.

Founded in 2018, Netris develops networking software for neoclouds, sovereign AI operators, AI factories, and AI platform providers through NAAM, short for Network Automation, Abstraction, and Multi-Tenancy. The product is designed to help operators deploy and run increasingly complex GPU networking environments without turning every infrastructure build into custom manual work.

The round also brings Guido Appenzeller, Partner at Andreessen Horowitz, onto the Netris board. His background in cloud networking and infrastructure makes the board addition more than a ceremonial funding-note detail.

The broader implication extends beyond one funding announcement. As AI infrastructure matures, competitive advantage is shifting from simply acquiring GPUs toward orchestrating, automating, and efficiently operating the networking layers that allow those GPUs to deliver value at scale.

What Happened

Netris announced a $15M Series A led by Andreessen Horowitz, adding new capital to expand engineering, strengthen commercial operations, broaden hardware support, continue enhancing its software platform, and grow internationally, including a Singapore expansion planned for 2026.

The funding fits a larger AI infrastructure pattern. Companies raced to secure GPUs during the first wave of generative AI buildout. The next phase is about making that compute usable, isolated, automated, and efficient enough for production workloads.

Unlike AI infrastructure companies competing mainly on hardware ownership, Netris is building software designed to orchestrate the networking environments that support modern GPU clusters. That is a quieter part of the market, but it is increasingly central to whether AI infrastructure can scale.

What Netris Actually Builds

Artificial intelligence infrastructure has become synonymous with GPUs. That makes sense. GPUs are visible, expensive, and easy to understand.

Networking rarely gets the same attention, even though it often determines whether those GPUs work together efficiently. Large AI clusters are not just collections of chips. They are complex systems of compute, storage, orchestration, tenancy, and network fabrics that need to operate together under pressure.

Netris addresses that challenge through its NAAM platform. According to the company's published materials, NAAM provides a unified control plane across multiple networking fabrics while enforcing hard multi-tenancy directly on networking hardware. It supports technologies including Ethernet, NVIDIA Spectrum-X, NVIDIA Quantum InfiniBand, NVL72, NVIDIA BlueField DPUs, and virtual and edge networking.

The objective is straightforward: help AI infrastructure operators launch GPU clouds faster, automate tenant provisioning, isolate workloads, and dynamically manage infrastructure utilization without turning every deployment into a bespoke engineering project.

That matters because networking complexity scales almost as quickly as GPU capacity. Adding more compute rarely makes operations simpler.

Why This Funding Matters

The numbers reported by Netris suggest the company is finding meaningful traction. Netris reports 800% ARR growth during the past 12 months, 35+ live deployments worldwide, and 12% of the neocloud market based on company-reported metrics.

Its customer list includes Lightning AI, TensorWave, STN, Boost Run, TELUS, DCAI, YOTTA, Visionbay.ai, Firmus, and HPE. The surrounding ecosystem includes partnerships and integrations spanning NVIDIA, Mirantis, Rafay, Red Hat, Spectro Cloud, vCluster, and HPE.

Those names matter because infrastructure software rarely succeeds in isolation. It becomes more valuable when it integrates across vendors rather than forcing operators to replace the systems they already rely on.

TechCrunch reported that Netris plans to use the round to hire more engineers and sales staff, support more hardware vendors, and add more functionality to its algorithm. That lines up with the company's own stated focus on team expansion, partner ecosystem growth, and global presence.

Market Context

The AI conversation has largely revolved around chips. That was natural during the first wave of generative AI adoption, when demand dramatically outpaced supply. Now the conversation is changing. The question is no longer only, "How do we buy GPUs?" It is, "How do we operate thousands of them efficiently?"

That distinction creates a different software opportunity. Netris positions NAAM as a purpose-built platform for AI-era networking rather than a retrofit of networking models designed for traditional enterprise infrastructure.

Whether operators are building neoclouds, sovereign AI environments, or AI factories, networking automation increasingly becomes a prerequisite rather than a convenience. The industry's pressure points are moving higher up the software stack.

Competitive Landscape

Guido Appenzeller joining the board is strategically relevant. His experience spans decades of networking innovation, including work across cloud infrastructure and virtualization. For a company focused on automating AI networking, that expertise directly matches the technical thesis.

The announcement also reinforces how venture capital continues investing deeper into AI infrastructure. Instead of concentrating only on foundation models or GPU manufacturers, capital is increasingly targeting the software layers that make complex infrastructure usable at enterprise scale. Netris is operating in that layer. It is not trying to make AI infrastructure louder. It is trying to make it work.

What This Signals

Every technology cycle eventually reaches the same point. The flashy layer attracts attention first. The infrastructure layer becomes indispensable later.

GPUs remain essential, but software increasingly determines whether expensive compute resources operate efficiently or sit idle behind operational complexity. Netris is positioning itself around that reality.

The company is focused on simplifying the operational side of AI infrastructure while enabling multi-tenant environments across sophisticated networking architectures. If the next phase of AI centers on production-scale infrastructure rather than experimentation, network automation becomes far more important than most headlines suggest.

Sometimes the biggest opportunities exist where fewer people are looking. Networking has never been particularly glamorous. It has always been indispensable.