Hardware–software
co-optimization for AI Workloads
Decart Optimization Stack (DOS) extracts every last drop of performance from your chips. We help AI labs, cloud providers, and chip manufacturers improve the performance of their most important workloads across GPUs, TPUs, Trainium, AMD chips or any other accelerator or platform.
Grounded in deep hardware expertise and co-design across leading accelerator platforms, our team of low-level engineers optimize for latency, throughput, utilization, and TCO, with a focus on agents, world models, and other low-latency AI workloads.
What you get
An end-to-end optimization stack that makes AI workloads faster and cheaper — through benchmarks, custom tuning, cross-hardware gains, and built-in profiling tools.
Faster time to market
Compress months of low-level tuning into weeks using proven, production-tested optimization playbooks.
Full hardware utilization
Extract peak performance from every chip across inference and training workloads.
Step-function cost reduction
Achieve order-of-magnitude efficiency gains that directly translate into lower TCO and durable competitive advantage at scale.
Let's build
something fast together
Whether you're looking to run a scoped milestone-based pilot or explore a long-term strategic partnership – we'd love to understand your workload and show you what's possible.