Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Securing LLM Workflows with Protegrity AI Developer Edition Learn how to protect sensitive data and prevent malicious prompt injections in your AI applications. In this technical walkthrough, Dan Johnson, Software Engineer at Protegrity, demonstrates a dual-gate security architecture designed to safeguard Large Language Models. Discover how to implement a security gateway that sits between your users and your LLM. This demonstration covers the integration of semantic guardrails and classification APIs to ensure data privacy and system integrity.

Want to test Protegrity’s data protection features without any local installation? In this tutorial, Dan Johnson shows you how to make your first protect and unprotect API calls directly in your browser using our interactive Jupyter Notebook (Binder). This is the fastest way to see Protegrity’s Python SDK in action—authenticating, applying protection policies, and maintaining data utility in real-time.