VeloxX is developing an inference architecture that keeps model weights close to computation, reducing the energy and bandwidth spent moving data.
Conventional inference repeatedly moves model weights through expensive memory hierarchies. That movement consumes bandwidth, energy, and data-center power.
Keeping persistent weights close to purpose-built compute can reduce movement through the model-weight path and free system resources for useful inference work.
Our A2I architecture brings purpose-built AI computation close to persistent memory, addressing the data-movement tax in today's inference systems.
Model parameters remain close to the compute resources that use them.
Purpose-built computation targets the AI matrix operations central to inference.
Designed for deployment from constrained systems to data-center infrastructure.
A system architecture designed around persistent model weights, local data handling, and efficient AI computation.
Persistent memory
Local data
AI compute
The architecture is designed to retain weights close to where recurring inference work is performed.
Efficient mixed-signal computation is placed close to persistent memory to reduce repeated model-weight traffic.
A modular system concept supports a range of inference deployments while preserving a common architectural foundation.
VeloxX is focused on reducing model-weight movement through persistent memory, efficient computation, and system-aware design.
Conventional accelerators repeatedly fetch model weights through the memory hierarchy.
Keep persistent weights close to the compute resources that use them.
General-purpose compute carries energy and data-movement overhead for recurring inference operations.
Use purpose-built mixed-signal computation for core AI matrix operations.
Memory bandwidth, power delivery, and cooling increasingly constrain inference growth.
Build a modular architecture designed around the realities of deployed AI systems.
VeloxX is developing and validating its first-generation architecture and software platform with prospective technology and deployment partners.
System concept defined
Core approach modeled
Integration path defined
Platform in development
Validation discussions underway
Our team brings experience from leading semiconductor, memory, computing, and AI companies, combining system architecture, mixed-signal design, software, and product execution.
We are engaging with memory partners, system companies, AI infrastructure providers, and strategic investors. Detailed architecture and performance materials are available in qualified discussions under NDA.