As more teams build internal AI agents powered by large language models (LLMs), they’re running into a critical challenge: securing the sensitive data behind those apps.

These agents often rely on Retrieval-Augmented Generation (RAG) frameworks and connect to production databases like MongoDB Atlas, creating new risks around access control, credential management, and data leakage.

This webinar covers:

• How users building RAG frameworks in MongoDB Atlas can secure their databases with HashiCorp Vault
• The biggest security challenges when building AI tools internally — and how to tackle them
• How to build a roadmap for implementing and optimizing key Vault features to secure your MongoDB Atlas deployment
• How to use Vault to store and manage access credentials, auto-rotation, and dynamic secrets