HomeAbout Us
Edge AICustom ASICsSystem SoftwareCo-Design

About XgenSilicon

We build complete System Software stacks and custom ASICs for Edge AI — co-designed from day one so every layer of silicon and software is aware of every other.

// Who We Are

Silicon and Software, Built as One System

XgenSilicon is an ASIC chip vendor building complete System Software stacks and custom ASICs targeted for Edge AI applications. We believe the next frontier of AI performance isn't in the cloud — it's at the edge, running on silicon purpose-built for each model.

Our hardware-aware ML compiler, RL-driven hardware architecture search, and proprietary HW Foundation Library — comprising a custom Network-on-Chip (NoC), purpose-built accelerator blocks, and a tightly integrated memory subsystem — work together as a vertically integrated chip design. The result: silicon and software built for a specific AI workload, with no wasted capacity from general-purpose design assumptions.

Founded in 2025 in Santa Clara, CA by Steve Xu and Ravindra Ganti, we work with innovators across autonomous systems, robotics, industrial IoT, and consumer electronics who need differentiated silicon to win their markets.

Follow on LinkedIn

Full-Stack

System Software

Compiler · Runtime · Toolchain

RL-Driven

HW Architecture Search

Automated PPA Optimization

Custom

HW Foundation Library

NoC · Accelerators · Memory Subsystem

Edge-First

Design Philosophy

Low Power · Low Latency · Privacy

// Why It Matters

The Model-to-Silicon Difference

In traditional chip development, model requirements, software architecture, and hardware specs are each locked in before the next layer can react. By the time incompatibilities surface, re-spins are expensive. XgenSilicon eliminates those one-way boundaries entirely.

Model-In to GDSII-Out

A tightly integrated flow that takes an AI model specification and produces tape-ready silicon — eliminating the manual handoffs between design stages that cost months and leave efficiency on the table.

AI-Driven Architecture Search

Proprietary AI methods explore the space of custom hardware architectures to find optimal PPA solutions for each target workload — automatically.

Proprietary Silicon IP Library

A purpose-built library of silicon building blocks, each designed with its software interface in mind so the compiler and the chip share a common language from day one.

Model-to-Silicon Co-Optimizing Compiler

Our compiler is built to understand the exact silicon it targets — code generation is derived for each custom ASIC, not a generic backend.

// Leadership

TrueASIC Lab

Semiconductor veterans, compiler engineers, and silicon designers united by a single conviction: the model must shape the silicon, and the silicon must shape the model — from specification to tape-out, every layer co-designed as one.

Steve Xu

Andrew Cilker

Jillian Yang

Dmitri Khokhlov

Ready to partner with XgenSilicon?

Tell us about your edge AI application. We'll show you how co-designing the System Software stack and custom ASIC together gets you to silicon faster.