Network infrastructure firm NetBox Labs closed a $35 million Series B funding round.

The round was led by U.S. investment firm NGP Capital, included Sorenson Capital and Headline as new investors, and had participation from existing investors including Two Sigma, Salesforce, and IBM.

New York-based NetBox spun out of managed DNS provider NS1 in early 2023 following NS1's acquisition by IBM. NetBox quickly announced a $20 million Series A that included participation from NS1 and IBM.

As the company told SDxCentral on completion of the Series A round, NetBox eyed a broader market than NS1, whose core business focused on internet traffic and routing management.

The firm is the commercial steward of the open source NetBox project, which positions itself as providing the “source of truth” to enable network automation, replacing legacy tools.

The NetBox offering includes IP address management and data center infrastructure management capabilities, alongside a series of APIs and integrations for network automation.

“We’re building dozens of new AI data centers every year, full of complex infrastructure," Jim Julson, head of network for CoreWeave, noted in a statement tied to NetBox's latest funding news. "NetBox is crucial for accelerating our timelines with automation.”

NetBox, earlier this year, launched a model context protocol (MCP) server, allowing large-language models (LLMs) the ability to directly interact with data from NetBox. The offering follows last year’s release of its NetBox Operator agentic AI tool.

AI is increasingly forcing data center and network owners to re-evaluate their current technology choices and how they will be positioned to face AI-driven networking demands.

Dell’Oro Group in a recent report found that global data center capex increased 51% in 2024, hitting $455 billion in investment last year. Custom accelerators from Amazon Web Services (AWS), Microsoft, and Google Cloud accounted for more than half of that total investment, with the hyperscalers bolstering their support for AI training workloads in 2024.