Impart LLM Security is a runtime defense platform designed to protect LLM and AI applications from security threats. The platform uses Attack Embeddings Analysis to detect prompt injection, jailbreaks, and sensitive data leakage within LLM application queries and responses. The solution provides automatic discovery of active LLM models across an organization, offering visibility into which teams and applications are using which models. It tracks usage patterns and identifies unauthorized deployments that could create security risks. The platform performs token-based query detection to analyze unstructured queries and identify malicious intent. It detects prompt injection, system prompt leakage, jailbreak attempts, and other LLM-specific attacks that traditional security controls like WAFs cannot detect. The system breaks down LLM queries into tokens and analyzes prompts at the token level for high accuracy detections without relying on regex rules. Impart LLM Security includes content safety controls to prevent harmful or inappropriate AI outputs from reaching users. It automatically filters responses that don't align with brand values or contain toxic content. Organizations can set custom policies for content moderation and receive alerts when responses violate standards. The platform identifies AI usage that violates security and content policies, detects teams using unapproved models, and prevents content that does not conform with brand guidelines. It monitors usage patterns and costs across both commercial and open-source models.