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Model

Discovery Model

The foundational model of the AgenticSafe framework. It establishes continuous visibility into every AI agent operating across your applications, APIs, workflows, and data, so nothing runs unseen.

Overview

The Discovery Model eliminates blind spots by continuously discovering every AI agent, known and unknown. That includes internal, external, third-party, partner, shadow, and dormant agents, giving you complete oversight of your entire AI ecosystem. It builds an immediate inventory of that ecosystem through both historical ingestion and real-time interception.

Capabilities

Semantic interception at inception

Monitors live traffic at the semantic level to identify and register each new agent the moment it first attempts to communicate with an LLM.

Historical log ingestion

Scans past conversation logs to surface hidden shadow agents, map prior usage patterns, and set a behavioral baseline for previously untracked systems.

Deployment

The Discovery Model is containerized and ready for cloud or on-prem:

  • On-premises, customer-managed, with full data residency
  • Public cloud across AWS, Azure, or GCP
  • Hybrid or private cloud for mixed infrastructure