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Revolutionizing Edge AI With Per-Model ASIC
"Reducing power, cost, and development time for edge LLM deployment".

"Reducing power, cost, and development time for edge LLM deployment".
XgenSilicon is an ASIC chip vendor building an automated hardware–software platform for deploying AI models on custom edge ASICs. Our platform integrates a hardware-aware machine learning compiler, reinforcement learning–driven automated end-to-end flow from Model-In to GDSII-out with learned optimizations, and a library of scalable RISC-V–based accelerator building blocks to transform high-level AI models into silicon-optimized implementations.
Using Reinforcement Learning and learned cost models, XgenSilicon automatically explores architecture, scheduling, and mapping decisions to optimize power, performance, and area (PPA). By tightly integrating model compilation with ASIC design automation, we streamline the full flow from Model-in to GDSII-out, reducing development cycles and accelerating edge AI deployments in ASICs.

Our mission is to make custom AI hardware accessible, efficient, and scalable for edge applications. We aim to eliminate the traditional barriers between AI model development and silicon realization by automating optimization across the entire stack—software, architecture, and hardware.
By enabling faster design cycles, predictable power and performance outcomes, and seamless deployment on custom ASICs, XgenSilicon helps innovators bring differentiated Edge AI products to market with confidence.

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