Insider Brief
- GigaIO has raised $21M in the first tranche of its Series B to scale production of its AI inferencing products SuperNODE™ and Gryf™, and expand sales, marketing, and R&D.
- Its vendor-agnostic platform supports GPUs from multiple providers and uses the patented FabreX™ memory fabric to deliver scalable, efficient AI infrastructure from edge to core.
- The company positions itself as a foundational player in next-gen AI infrastructure, with strong investor backing and plans for a second close of the Series B round.
PRESS RELEASE — GigaIO, a leading provider of scalable infrastructure specifically designed for AI inferencing, announced it has raised $21 million in the first tranche of its Series B financing. The round was led by Impact Venture Capital, with participation from CerraCap Ventures, G Vision Capital, Mark IV Capital, and SourceCode Cerberus.
The new funding will enable GigaIO to expand production of its flagship products SuperNODE™ and Gryf™ and accelerate innovation with a clear focus on AI inferencing. Funding will be used to:
- Ramp up production of SuperNODE, the most cost-effective and energy-efficient infrastructure designed for AI inferencing at scale.
- Accelerate the deployment of Gryf, the world’s first carry-on suitcase-sized AI inferencing supercomputer, which brings datacenter-class computing power directly to the edge.
- Invest in new product development to broaden GigaIO’s technology offerings.
- Expand the sales and marketing teams to serve the increasing demand for vendor-agnostic AI infrastructure.
“We are thrilled to achieve this milestone with the support of Impact Venture Capital and our investors,” said Alan Benjamin, CEO of GigaIO. “With SuperNODE and Gryf, we have created a new paradigm for cost-effective and power-efficient AI inferencing infrastructure. Our vendor-agnostic platform uniquely frees customers from dependency on single-source AI chips and architectures. Whether it’s GPUs from NVIDIA and AMD or new AI chips from innovators like Tenstorrent and d-Matrix, GigaIO enables customers to leverage the best technologies without vendor lock-in. This funding gives us the fuel to move faster and meet the surging demand.”
GigaIO’s patented FabreX™ AI memory fabric architecture enables the scale-up and dynamic composition of compute, GPU, storage, and networking resources — unlocking performance and cost efficiencies that traditional architectures are unable to deliver. As AI models grow larger and more complex, FabreX provides the flexibility needed to scale infrastructure on demand, at the rack level and beyond.
“GigaIO’s innovative infrastructure is precisely what businesses need to harness the transformative power of AI,” said Jack Crawford, Founding General Partner at Impact Venture Capital. “As enterprises and cloud providers race to deploy AI at scale, GigaIO delivers a uniquely flexible, cost-effective, and energy-efficient solution that accelerates time to insight. We believe GigaIO has assembled a world-class team and is poised to become a foundational pillar of tomorrow’s AI-powered infrastructure, and we’re proud to back their vision.”
GigaIO plans to complete a second close of the Series B in the coming months, citing continued strong interest from strategic and financial investors. Rockefeller Capital Management’s Investment Banking division served as the exclusive advisor to GigaIO in the transaction.
About GigaIO
GigaIO redefines scalable AI infrastructure, seamlessly bridging from edge to core with a dynamic, open platform built for every accelerator. Reduce power draw with GigaIO’s SuperNODE, the world’s most powerful and energy-efficient scale-up AI computing platform. Run AI jobs anywhere with Gryf, the world’s first suitcase-sized AI supercomputer that brings datacenter-class computing power directly to the edge. Both are easy to deploy and manage, utilizing GigaIO’s patented AI fabric that provides ultralow latency and direct memory-to-memory communication between GPUs for near-perfect scaling for AI workloads. Visit www.gigaio.com, or follow on Twitter (X) and LinkedIn.
Contact:
Shannon Biggs 760–487–8395
[email protected]
