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.
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 composable custom hardware block library work together as a vertically integrated co-design platform. The result: purpose-built silicon and software that maximizes performance and power efficiency for each specific AI workload — performance no general-purpose chip can match.
Founded in 2025 in Santa Clara, CA, we work with innovators across autonomous systems, robotics, industrial IoT, and consumer electronics who need differentiated silicon to win their markets.
Full-Stack
System Software
Compiler · Runtime · Toolchain
RL-Driven
HW Architecture Search
Automated PPA Optimization
Custom
HW Block Library
Composable Accelerators
Edge-First
Design Philosophy
Low Power · Low Latency · Privacy
The Co-Design Difference
Traditional chip development runs software and hardware in separate, sequential phases. Every handoff between teams leaves efficiency on the table. XgenSilicon eliminates those 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.
RL-Driven Architecture Search
Reinforcement learning agents explore the vast design space of custom hardware architectures, dataflow scheduling, and block mapping to find Pareto-optimal PPA solutions automatically.
Hardware-Aware ML Compiler
Our compiler understands the target silicon at every layer — operator fusion, memory tiling, dataflow scheduling — producing maximally efficient inference kernels for each specific ASIC.
Edge-First by Design
Every architectural decision is made with power envelope, latency budget, and on-device privacy in mind. Cloud-first assumptions don't apply — and we never make them.
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.