Where could work data go?
Review personal accounts and declared connections before assuming company protections apply.
Holistic AI EndLayer / Shadow AI detection
Shadow AI detection.
Shadow AI detection.
Know what’s really there.
Find AI tools, coding agents, local models and MCP connections across enrolled devices. Connect each discovery to its account and declared access so your team knows what to review next.
From scattered signals to a connected AI inventory
01 / On the device
03 / A record you can review
● Discovered
Coding agent found
- Device
- Example laptop / enrolled
- Account
- Personal account
- Context
- Configured unattended mode
- Review
- Not yet on the approved list
Next decision
Confirm the owner and review permitted agent behaviour.
Illustrative discovery · select a signal to exploreObserve → Connect → Review
Visibility before controlAI adoption moves faster
AI adoption moves faster
than your approved list.
What is Shadow AI detection?
Shadow AI is AI used for work without the organisation’s knowledge or approval. It is the part of shadow IT that involves AI. Shadow AI detection, also called shadow AI discovery, identifies that activity and its context so IT, security and AI leaders can bring it into an accountable inventory.
A personal AI account, an unreviewed coding agent or a local model can sit outside procurement records. Finding it is the first step toward deciding whether to enable it, limit its access or investigate further.
What can an agent reach?
MCP hosts, repositories and configured autonomy add context that an app name alone cannot explain.
Who owns the usage?
Use discovery as the starting point for usage attribution, reviews of overlapping tools and AI investment decisions.
What EndLayer discovers
Beyond a list of AI apps.
Surface connects supported local signals. Keep the tool, device, account and configured reach together when reviewing a discovery.
AI tools & coding agents
Identify supported installations and configured permission or modes for unattended operation.
MCP servers & repositories
See declared Model Context Protocol (MCP) hosts and project connections. Configuration describes potential reach, not proof of access.
API keys & account context
Find credential presence and available work, personal or unknown account context. Employee attribution needs a reliable identity mapping.
Local models & browser AI
Discover supported runtimes, models and browser signals alongside desktop tools.
Coverage depends on the operating system, tool and enabled collectors. Unenrolled devices and unavailable checks must remain visible as gaps.
Explore the 21 signals ↗How Shadow AI detection worksFrom one endpoint
From one endpoint
to an informed decision.
Enrol the device. Read the signals. Add the context. Decide what belongs. Discovery and enforcement are separate steps.
- 01 / Enrol
Start on the device.
Install the Layer 1 Agent on supported devices. Agree collection settings and confirm the first report.
Agent installation ↗ - 02 / Discover
Read local signals.
Find supported tools and configuration without executing the discovered tools or integrating each tool’s API.
Surface capabilities ↗ - 03 / Connect
Make it reviewable.
New reports refresh the inventory. Review source, account, declared access and last report; a silent device is not a clean device.
Understand the context ↗ - 04 / Review
Give it an owner.
Compare with policy, assign the next action and retain evidence. Use Govern for supported policy controls.
Apply your rules ↗
Choose the right visibilityA network view and a device view
A network view and a device view
answer different questions.
Build on your existing security stack. Evaluate what each source actually observes, rather than assuming one view covers all AI use.
Discovery sourceUseful forQuestion to validate
SSO & procurement
Known accounts, purchases and approved services.
What sits outside managed sign in or purchasing?
Network, proxy & CASB
AI service traffic visible to the configured collection path.
What local models or configuration are outside that path?
EndLayer endpoint discovery
Supported local tools, models, accounts, keys and MCP configuration.
Which devices, tools and collectors are reporting?
Cloud services and instrumented applications extend the platform through separate sources. Discovery does not replace your EDR, DLP or device management.
Check deployment & coverage ↗Credential presence, not secret values.
Investigate that a key is configured without putting the key itself in the discovery record.
Metadata before conversation content.
Discovery reads supported configuration. Prompt and response collection is off by default; local request inspection is a separate capability.
Evidence with its limits intact.
Review source, last report and unknown states. Set access and retention expectations with your deployment team; findings support governance, not automatic compliance.
Regulation & governanceYou cannot assess
You cannot assess
AI you cannot see.
Shadow AI can create gaps in regulatory oversight. Applicable duties depend on your location, role, data and use case. Discovery gives your teams evidence to start that assessment.
Requirement or frameworkWhat your team must considerHow discovery helps
Providers and deployers in scope must take measures to support staff AI literacy. Other duties depend on the system, its use and your role.
Identify AI tools and their context so owners can review intended use, assess applicable obligations and direct relevant staff training. Discovery does not perform the legal classification.
Where personal data is processed and the relevant law applies, assess lawful basis, transparency, security and accountability. Complete a data protection impact assessment where required.
Find tools, personal accounts and declared connections that need a data protection review. Your team still needs to establish what data is processed, by whom and for what purpose.
The framework recommends mechanisms to inventory AI systems, with resources aligned to organisational risk priorities. It is voluntary guidance, not a law or certification.
Use discoveries as inputs to your AI inventory. Add business purpose, ownership and review decisions through your governance process.
EndLayer supports evidence gathering and review. Discovery alone does not establish compliance. Your legal and governance teams determine which obligations apply and what further action is needed.
Explore governance & evidence ↗Regulatory context reviewed 30 October 2026. Follow the linked authorities for current guidance.
Cost & business caseScope the discovery.
Scope the discovery.
Then size the investment.
What does Shadow AI detection cost? Request a quote for your environment and agree the scope before comparing options. No published price per device is quoted here.
Your evaluation budget
01Platform scopeFleet, capabilities and commercial terms
02Rollout effortPackaging, enrolment and compatibility testing
03Operating effortFinding review, remediation and ownership
Discuss scope & pricing ↗Prove usefulness in a focused pilot.
- Choose representative devices and the tools you already know about.
- Check discoveries, reporting gaps, collection settings and device impact.
- Measure time to build the inventory and review unapproved tools.
- Assign owners and agree what must change before expanding.
For cost savings, connect available usage to licence and provider records. Discovery alone does not measure token waste or prove ROI.
Explore AI usage, FinOps & ROI ↗Five practical answers
Before you start.
Coverage, setup, privacy, control and cost. These are the details to settle in your evaluation.
Can EndLayer discover ChatGPT, Claude, Cursor and other employee AI tools?
EndLayer discovers supported AI applications, coding agents and browser AI signals on enrolled devices. Ask for coverage of your exact tools, versions and operating systems, including ChatGPT, Claude or Cursor if they are in your environment. An installation or browser signal is not proof that every conversation has been observed.
Do we need an integration for every AI tool?
Endpoint discovery reads supported local signals through the Layer 1 Agent without a separate API integration for each discovered tool. Enrolment is still required. Cloud connections and application instrumentation are separate sources with their own setup and coverage.
Does Shadow AI detection read prompts, source code or API key values?
Discovery focuses on tool and configuration metadata. Credential presence is reported without the secret value; repository context is not collection of source code. Prompt and response collection is off by default and requires an administrator choice. Agree access, retention and reporting settings before rollout.
Can we block unapproved AI after discovering it?
Use discovery findings to decide what to approve, investigate or disallow. Govern can apply configured controls to supported AI interactions. Blocking a request, preventing an app from launching and uninstalling it are different actions; validate the action you need for each tool and host.
How quickly can we start, and what does Shadow AI detection cost?
Start with a representative set of enrolled devices and compare the findings with known tools. Confirm reporting cadence, compatibility and device impact during the pilot. Request a scoped quote covering your fleet, capabilities and deployment needs; this page does not publish a price per device or guaranteed rollout time.
EndLayer
Give AI room to work.And clear boundaries.
See the Guardian Agent Platform on your own fleet. Find every AI tool, understand what it reaches and costs, and apply the controls your team needs.
One connected layer of control
Devices · Cloud · ApplicationsSurface / Monitor / Govern