‍What's launching

While traditional EDR and XDR platforms treat agents like generic applications, Shadow AI is built around the AI agent lifecycle from the start: how agents plan, act, call tools, and evolve over time.

Shadow AI surfaces AI wherever it hides, across agents, apps, extensions, and pipelines. It also goes beyond agents, monitoring outbound network connections, application behavior, and installed package telemetry to identify AI usage. 

If someone in your environment is using AI or deploying an agent, Shadow AI is built to catch it.

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Read the launch announcement: [PRESS RELEASE LINK]. 

How Shadow AI finds the AI agents you don't know are running

Security teams have no reliable way to know how many AI agents are running across their environment. Existing tools were not built to look for them.

Shadow AI was built from the ground up to find AI agents within your enterprise. It deploys as a lightweight endpoint collector and runs on Linux, macOS, and Windows alongside your existing EDR or independently. It knows what AI looks like at the system level and collects those signals directly across every endpoint, covering the range of AI activity enterprises actually face: commercial tools like ChatGPT, Claude, and Copilot, self-hosted models, browser extensions, IDE plugins, and the informal agentic pipelines that generic tools fail to classify as AI at all.

The result is a comprehensive inventory of AI usage across your environment without maintaining domain allowlists or waiting for a breach to surface the activity. It works even when agents talk to unknown endpoints or self-hosted models. No domain allowlist required.

How Shadow AI shows you what every agent is actually doing

Knowing an AI tool exists is not enough. Security teams need visibility into what agents are doing, whether that behavior is safe, and whether it has changed.

Agent Behavior Analysis captures the full behavioral sequence of agents. Not just individual events, but the order, structure, and context of actions across process, network, and file activity. It reasons over how an agent's actions connect, not whether they match a known signature. The Shadow AI Dashboard maps this across your entire environment, including which agents are active, on how many devices, and exactly which policy triggered a flag. Analysts can pull the complete agent action trajectory the moment something looks wrong.

Instead of triaging isolated process events, security teams get the full story of what an agent did and why it was flagged, cutting investigation time and the guesswork that leads to missed incidents or false escalations. When agent behavior drifts or something genuinely goes wrong, teams know immediately, with the context to act.

When an agent misbehaves, you need to know what it did, what it touched, and how far it got. Shadow AI maintains a continuous operational record, including host, user context, tool calls, and sequence, so your team starts an investigation with evidence, not questions.

How Shadow AI fits the security stack you already run

Security teams are already stretched thin, managing countless security tools and SaaS platforms. Adding another tool that does not integrate means more work, not less risk.

Shadow AI integrates natively with leading EDR, XDR, and enterprise SaaS platforms, including CrowdStrike Falcon and Microsoft Defender, with additional connectors added on an ongoing basis. Data sources are normalized into a single pipeline for agent pattern detection. It captures data across endpoints with or without a commercial EDR already in place.

Security teams work from one unified view across endpoint and SaaS signals, without rebuilding detection logic for each data source or managing separate dashboards per vendor.

Where Shadow AI fits in the Virtue AI ecosystem

Shadow AI is a layer within AgentSuite-Blue, Virtue AI's end-to-end, multi-layered security and governance suite for agentic systems, on prompt, action, MCP, and skill levels. Shadow AI handles the discovery layer: knowing which agents are running and what they're doing in the first place.

It works alongside the other AgentSuite-Blue layers. ActionGuard monitors agent behavior as it happens and blocks malicious tool calls before they fire, which is where active blocking lives once Shadow AI has surfaced what's running. MCPGuard scans MCP tools and source code for hidden prompt injections, vulnerabilities, and data-leakage paths. Together they form the defense side of Virtue AI's two-sided model, the runtime security and governance counterpart to the AgentSuite-Red red-teaming platform.

See Shadow AI in your environment

With Shadow AI, security teams get a comprehensive inventory of AI usage across their environment so they can reduce risk and continue innovating.

Read the launch announcement: [PRESS RELEASE LINK]. 

To see what a full inventory of AI usage looks like across your endpoints, request a demo: [DEMO LINK].