Normal EDA proves what works and explores what's possible in silicon. It learns continually, post-training our AI models on your design data and your team's implicit knowledge, deployed on-premises.



AI co-designed silicon built on new device physics. Partnering with the world's most advanced institutions.

Normal EDA proves what works and explores what's possible in silicon. It learns continually, post-training our AI models on your design data and your team's implicit knowledge, deployed on-premises.







Normal ASICs build what Normal EDA makes possible: custom silicon, with novel device physics, built toward a 10-100× gain in AI inference per dollar, per watt. Designed to break the long-context wall, and scale to future multi-modal and world modeling workloads.
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Normal is built by engineers at the frontier of physical and mathematical intelligence: co-creators of core TensorFlow frameworks, co-founders of Meta's Probability team, architects of Google's first production-scale AI deployments, pioneers of NISQ at Los Alamos, and co-designers of Haskell and C#.
Our silicon team built the chips that power modern computing: CPU and GPU IP at NVIDIA and Apple, AI accelerators at Graphcore, and tape-outs across analog and mixed-signal designs. Alongside these builders are operators who took frontier work to market from zero to one at Palantir, Google X, and high-growth deep tech companies.
