Summary:
- GigaIO, a Carlsbad-based provider of scalable infrastructure for AI inferencing, secured $21M in the First Tranche of its Series B funding.
- The funding round was led by Impact Venture Capital, with participation from other investors like CerraCap Ventures and G Vision Capital.
- GigaIO plans to use the funds to expand production of its flagship products SuperNODE and Gryf, focusing on accelerating innovation in AI inferencing.
Article:
GigaIO Raises $21M in Series B Funding for AI Infrastructure Expansion
GigaIO, a leading provider of scalable infrastructure for AI inferencing based in Carlsbad, California, recently announced the successful raise of $21 million in the First Tranche of its Series B funding round. The round was led by Impact Venture Capital, with additional investments coming from CerraCap Ventures, G Vision Capital, Mark IV Capital, and SourceCode Cerberus.
The company, under the leadership of CEO Alan Benjamin, plans to utilize the funds to ramp up production of its flagship products, SuperNODE and Gryf, while also focusing on accelerating innovation in the field of AI inferencing. Both SuperNODE and Gryf leverage GigaIO’s patented AI fabric technology to provide ultra-low latency and direct memory-to-memory communication between GPUs, enabling near-perfect scaling for AI workloads.
SuperNODE is an energy-efficient scale-up AI computing platform, while Gryf is a compact AI supercomputer designed to bring datacenter-class computing power directly to the edge. GigaIO’s FabreX AI memory fabric architecture allows for dynamic composition of compute, GPU, storage, and networking resources, delivering optimal performance and cost efficiencies as AI models continue to grow in complexity.
Looking ahead, GigaIO has plans to complete a second close of the Series B funding round in the coming months, further solidifying its position as a key player in the AI infrastructure space.
Stay tuned for more updates from GigaIO as they continue to drive innovation and scalability in the field of AI inferencing.