Executing AI Locally | Privacy-First AI for True Data Sovereignty

Explore how organizations can run AI entirely within their own environment to protect sensitive data and maintain full control. This webinar focuses on executing privacy first AI using locally deployed Small Language Models instead of cloud based Large Language Models, highlighting the security, compliance, and privacy risks that come with third party AI services. The session explains key differences between local and cloud AI approaches, including how generative and discriminative defense models are used in security workflows.

The discussion also looks at how in environment AI reduces external dependencies and prevents data from leaving organizational boundaries. Using Libraesva’s Semantic AI as an example, the webinar shows how advanced threat detection can be achieved without exposing email content or security telemetry to third party platforms, supporting stronger data sovereignty and trust.