Etched Raises $800M as AI Inference Infrastructure Demand Grows
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Etched, a San Jose-based company focused on AI inference infrastructure, has emerged from stealth after raising a total of $800 million across multiple funding rounds.
The company said its latest financing round closed in December 2025. The round brought in $500 million at a post-money valuation of $5 billion.
Investors in the company include Jane Street, Jump Trading, Two Sigma, Ribbit Capital, and Peter Thiel, among others. AI researchers and industry figures such as Geoffrey Hinton, Fei-Fei Li, and Andrej Karpathy also backed the company.
Focus on AI Inference Systems
Etched develops rack-scale inference systems designed to improve the speed and efficiency of AI model deployment. The company said its systems are built through hardware and software co-design across the full infrastructure stack.
The startup is led by Gavin Uberti and co-founder Rob Wachen.
According to the company, its systems currently support AI models including DeepSeek, Qwen, Mamba, and Llama. The infrastructure is designed to handle large-scale AI workloads and models with high parameter counts.
Expansion Across Manufacturing and Operations
Etched said it has signed more than $1 billion in customer contracts as demand for inference infrastructure increases.
The company also stated that it achieved first-pass silicon success on TSMC’s N4P process within three years of its seed funding. It is currently validating its first rack-scale product with customers.
In addition, Etched has established manufacturing operations in Taiwan and expanded facilities at its San Jose headquarters. These include a data center, test house, and prototyping lab for new product introduction (NPI).
The company said the integrated setup allows design, validation, and production activities to operate under one roof. It also outlined plans to scale operations further by 2027.
Team Expansion
Etched currently employs more than 400 people. The team includes professionals with prior experience at companies such as NVIDIA, Broadcom, Google, and SK Hynix.
The company said many team members previously worked on systems used for AI inference and large-scale computing infrastructure.
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