Use case: Shadow AI Agent Discovery

The agents running in your environment right now weren't approved by IT. Most of them weren't even reported.

Shadow AI has moved beyond employees using ChatGPT. It's autonomous agents with persistent memory, tool-calling capabilities, and access to your enterprise systems - deployed without security review, operating without governance, and invisible to every tool you already have. aizome surfaces every shadow agent within hours. No prior knowledge of which agents exist required.

What You Can't See Is Already Running

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30%Industry data, 2026

of organizations have full visibility into employee AI usage. The other 70% are governing a fraction of what's actually running.

40%Gartner, via Questa AI

of enterprise AI failures will involve shadow AI as a contributing factor by 2027.

48%Dark Reading, via Optro

of cybersecurity professionals rank agentic AI as the most dangerous attack vector of 2026.

Nothing Stays in the Shadows

Every agent. Every surface. No prior knowledge required.

Shadow agents don't register themselves. They appear on employee desktops, in SaaS platforms, connected via MCP servers and browser extensions, running on personal credentials against enterprise systems. aizome deploys an endpoint agent at the OS level and connects to your existing security stack - EDR, MDM, CASB, enterprise browsers, identity providers. Every agent surfaces within hours. Registered and shadow in a single inventory.

Every agent mapped to its owner, its systems, and its blast radius.

Only 24.4% of organizations have full visibility into which AI agents are communicating with each other. A shadow agent connected to Salesforce, Slack, and GitHub represents a blast radius most security teams have never quantified. aizome maps every agent to every system it touches - producing a live relationship graph of the entire agentic ecosystem across SaaS, on-premise, and legacy environments. Owner attributed. Risk scored. Blast radius visible.

Risk scored by what the agent can actually reach - not just that it exists.

Not all shadow agents carry the same risk. An agent connected to a payment system is categorically different from one monitoring competitor pricing. aizome scores every discovered agent against data sensitivity, system connections, and behavioral baseline - surfacing the highest-risk agents to the top of the priority queue. Context over alert flood.

Discovered. Assessed. Acted on - without leaving the platform.

Visibility without enforcement is a report. aizome lets you suspend an agent, reassign ownership, apply a scoped policy, or explore its full relationship map - all from the moment it's discovered.

Without aizome / With aizome

The difference shows up before the first incident does.

Withoutaizome

  • Shadow agents operate on full user credentials with no scope restriction
  • No visibility into which personal tools connect to which enterprise systems
  • Risk exists only on the agents IT knows about - which is a fraction of what's running
  • A shadow agent causes an incident - attribution is impossible, audit trail doesn't exist
  • Annual audits can't keep pace with agent fleets that double every four months

Withaizome

  • Every agent surfaced within hours - registered, shadow, and BYOA in one inventory
  • Every agent mapped to its owner, its systems, and its potential blast radius
  • Risk scored against data sensitivity and system connections - prioritized immediately
  • Actions taken in platform - suspend, scope, reassign - without a separate tool
  • Continuous discovery - new agents surface as they're deployed, not at next audit

Questions, Answered

What teams ask about shadow AI agent discovery. Talk to us

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