Fractile Raises $220 Million Series B Funding to Scale AI Inference Chip Production
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Fractile, a London-based AI hardware startup, has raised $220 million in Series B funding to accelerate production of its AI inference chips and computing systems.
The round was led by Accel, Factorial Funds, and Founders Fund, with participation from Conviction, Gigascale, O1A, Felicis, Buckley Ventures, and 8VC, alongside existing investors.
The company said it will use the funding to accelerate manufacturing and delivery of its first silicon chips and compute systems to enterprise customers.
Fractile Develops AI Inference Hardware
Founded in 2022 by CEO Walter Goodwin, Fractile develops semiconductor hardware designed to improve the speed and efficiency of AI inference workloads.
According to the company, its computing architecture focuses on addressing memory bandwidth limitations that affect large-scale AI systems and reasoning models.
Fractile said its hardware is designed to achieve processing speeds of up to 1,200 tokens per second, helping reduce the time required for large sequential reasoning tasks and multi-million-token workloads.
Funding to Support Chip Production and Expansion
The company plans to use the latest funding to expand production capabilities and support commercial deployment of its AI compute systems.
In addition, Fractile has expanded its engineering operations across the United Kingdom, the United States, and Taiwan.
The company said these locations support semiconductor development, foundry processes, and hardware engineering activities tied to its full-stack AI computing platform.
Growing Demand for AI Infrastructure
The broader AI infrastructure market has seen increasing investment in specialized chips and compute systems designed for AI training and inference workloads.
As enterprises deploy larger AI models, semiconductor startups are focusing on improving compute efficiency, memory performance, and inference speed to support commercial AI applications.
Fractile said it aims to position its technology as part of the next generation of AI computing infrastructure for enterprise-scale deployment.
