Standard Kernel Co. develops AI-driven software to improve performance across the accelerator stack, from applications and runtimes to low-level GPU kernels. The company’s systems analyze workloads, generate and test optimized code, and tune deployments for specific models, traffic patterns, and hardware. Its approach aims to unlock performance and cost efficiencies while supporting multiple accelerator architectures.

Products and services include Maison Token, an inference offering available through usage-based tokens or dedicated endpoints; an inference runtime licensed for use on customers’ own hardware; and Performance as a Service, which applies the company’s optimization system to customer workloads. Dedicated deployments can be tailored to a workload’s model, routing, and capacity needs.

Standard Kernel also conducts performance engineering engagements for applications such as quantitative trading, weather forecasting, and interactive world models. Its research and tools cover kernel optimization, profiling, PTX analysis, correctness checking, GPU benchmarking, and post-training for low-level performance reasoning. The company describes its team as having backgrounds in AI and systems research, GPU programming, compilers, and high-performance infrastructure.