We specialize in both Cloud and On-Premises TCO optimization, helping enterprises evaluate and optimize infrastructure costs across different deployment models to find the most cost-effective solution

Process and analyze complex infrastructure expenses, from model serving and training costs to storage and network costs, delivering comprehensive cost reduction strategies while maintaining performance

Track and optimize costs in real-time across your ML infrastructure, from training data storage to model serving expenses, ensuring efficient resource utilization and preventing cost overruns

Launch faster with Xenoss pre-built assessment frameworks designed for enterprise ML infrastructure. Quickly identify cost optimization opportunities and implement solutions to reduce TCO

Select the tools and platforms that best align with your enterprise’s ML infrastructure. Our engineers bring deep expertise across diverse technologies, ensuring optimal cost-performance balance regardless of your stack

Achieve up to 40% reduction in ML infrastructure costs through our optimization strategies, covering compute, storage, and operational expenses while maintaining model performance

Optimize costs while ensuring your ML infrastructure meets security and compliance requirements, implementing cost-effective security measures without compromising protection

Our engineers excel in ML infrastructure optimization, bringing experience from working with enterprises like Microsoft, Toshiba, and Activision Blizzard to deliver cost-efficient ML operations at scale