Fear Not! A Security Model for GenAI

The Generative AI revolution is transforming how organizations operate, unlocking new use cases across industries and employee workflows. However, challenges such as security, legal compliance, and demonstrating return on investment (ROI) hinder widespread adoption. One approach for solving some of these issues uses a security orchestration layer, enabling organizations to confidently connect any data source with any generative AI model. This approach lets businesses leverage the power of GenAI while maintaining control and confidentiality. Check out this episode of DMRadio to learn more as Host @eric_kavanagh interviews Oz Wasserman of Opsin. They'll discuss how retrieval-augmented generation (RAG) can be used to optimize the outputs of Large Language Models (LLMs). Combining contextual information with ongoing improvements in foundational models, RAG delivers superior results, ensuring organizations achieve tangible ROI with GenAI investments. Security features like role-based access control (RBAC), auditing, and anonymization can be used to safeguard data privacy and enhance security.