EDWIN AI SECURITY FAQ
Security, Data Handling, and Governance for Edwin AI
This FAQ provides an overview of LogicMonitor’s approach to securing and governing Edwin AI, including how customer data is processed, how large language models are used, and what controls are in place for access, retention, auditability, and availability.
Use this FAQ to understand Edwin AI’s current security model, data residency considerations, model provider approach, AI governance practices, and safeguards for enterprise IT environments.
Review how Edwin AI handles customer data, data isolation, encryption, credential storage, third-party subprocessors, and customer controls for limiting or stopping data flow into Edwin AI.
Understand Edwin AI’s LLM provider approach, how customer data is handled by model providers, whether data is used for model training, and how observability and trace-level logging support debugging, quality assurance, and performance optimization.
Learn how Edwin AI supports human-in-the-loop workflows, source references, guardrails for agent actions, model evaluation processes, staged rollouts, and high-availability architecture for large-scale alert environments.
