Large Language Models unlock powerful new capabilities, but they also introduce risks: prompt injection, data leakage, unsafe outputs, and compliance challenges. In this session, we’ll explore Google Cloud’s Model Armor, a new service that proactively screens LLM prompts and responses to ensure safety, privacy, and compliance. I’ll share real-world use cases, architecture patterns, and best practices for integrating Model Armor into enterprise AI systems—whether on GCP, multi-cloud, or hybrid environments. Attendees will leave with practical strategies to safeguard their AI applications and build trustworthy, scalable solutions.