SANTA CLARA, California: Upscale AI announced a $200 million Series A funding round on January 21, bringing total capital raised to over $300 million as the startup positions itself to solve critical networking bottlenecks in AI infrastructure.
The oversubscribed round was led by Tiger Global, Premji Invest, and Xora Innovation, with participation from Maverick Silicon, StepStone Group, Mayfield, Prosperity7 Ventures, Intel Capital, and Qualcomm Ventures. The company previously secured a $100 million seed round.
Upscale AI develops the SkyHammer system, specialized data center networking hardware and software designed specifically for large-scale AI workloads. The company argues that “traditional network architectures are fundamentally unsuited for the AI era,” according to the funding announcement published on Tech Startups.
The capital will accelerate product development and commercial deployment of Upscale’s open AI networking platform as enterprises face mounting infrastructure challenges. Yesterday’s funding announcement was part of what industry observers described as a concentrated investment day focused on infrastructure and “execution-heavy categories where scale creates defensibility,” including AI compute, data center networking, and production-ready AI systems.
The funding arrives as AI infrastructure spending surges globally. According to Carta data, investors deployed approximately $20 billion in software funding rounds across Q2 and Q3 2025 combined, marking “the fastest rate of spending since the first half of 2022.” The SaaS sector captured 33% of all venture funding logged on Carta in Q3 2025.
The networking infrastructure segment has emerged as a critical bottleneck as enterprises scale AI deployments. As cloud and AI workloads grow exponentially, traditional networking solutions struggle to handle the unique demands of distributed AI training and inference at scale.
Upscale AI’s approach focuses on purpose-built networking solutions that optimize data movement between GPUs and across data center clusters, addressing latency and throughput challenges that conventional networking equipment cannot resolve efficiently.
The Santa Clara-based startup joins a wave of infrastructure companies attracting significant capital as the AI industry matures beyond model development into production-scale deployment challenges.
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