As 80% of organizations identify AI agents as a top business priority, the challenge has shifted from simple experimentation to sustainable production. Yet, many enterprises remain stalled by the high cost and complexity of GPU-centric infrastructure.
This research presents a more practical path forward. It details how Private AI allows you to operationalize Small Language Models on powerful AMD EPYC CPUs, delivering the performance you need for chatbots and automation without the massive hardware overhead.
Read this research to:
- Capitalize on the 65% of enterprise data that currently remains on-premises without risky cloud migrations.
- Reduce TCO and energy consumption by running efficient models on CPUs rather than expensive GPU clusters.
- Deploy high-priority agents for knowledge management and process automation, leveraging your existing infrastructure.
