San Francisco startup Meter has just closed a $170 million financing round at a valuation north of $1 billion. Led by General Catalyst with participation from Microsoft, Sequoia Capital and other major backers, this investment spotlights a growing belief in AI’s next frontier: networking infrastructure. While most headlines focus on cutting-edge chips and giant language models, Meter is betting that faster, smarter data pipelines will make or break tomorrow’s AI applications.
$170M Series C Propels Meter to Unicorn Status
Meter was founded to overhaul the switches, routers and access points that shuttle massive AI workloads between data centers. As model sizes and computational demands surge, existing networks often become the bottleneck—no amount of chip power can fully compensate for clogged data paths. That reality convinced early believers from OpenAI, LinkedIn and Google Cloud to get on board, and it’s what drove General Catalyst’s Hemant Taneja to lead this round.
Overhauling AI Networking Bottlenecks
Incumbents like Cisco and Arista Networks are already racing to keep up—Cisco rolled out AI-optimized switches just last week—but Meter thinks it can win customers by blending hardware and software into a flexible, subscription-style offering. Enterprises craving cloud-scale performance without handing over full control of their on-premises infrastructure may find that proposition hard to resist.
Competitive Dynamics and High-Stakes Latency Race
With every microsecond of latency potentially translating to millions in savings, Meter’s fresh capital and high-profile supporters give it a running start. If networks truly become the unsung hero of AI, this funding could mark the moment when data plumbing finally steps into the spotlight—alongside GPUs and neural nets—as the key to unlocking next-generation intelligence.