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Discover / Shadow AI

Find the AI your inventory is missing.

Your teams adopt AI faster than a spreadsheet can follow. Bring signals from code, cloud and workplace apps into one queue, with the source behind every discovery.

See it with my teamSee it in action
Example data. A mention, a dependency or an authorised app is a lead for a person to review, not proof of use.
01

Signals with their source, ready for review.

02

Confirmed uses that enter the register.

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A shared queue with traceable decisions.

Live product

Find a signal. Decide what enters the register.

Discover brings the first clues together. Review the source, confirm the use case and turn a discovery into an owned AI system.

CONNECTED TO YOUR TEAM’S WORK

GitHubAWSAzureGoogle WorkspaceMicrosoft 365

WHAT YOU DO WITH FENCIA

From the first signal to an answer you can explain.

Explore the screens and the work behind each result.
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From discovery to a record with context.

Connect supported sources and review the signals they expose. A library, an authorised app or a cloud resource can start the conversation with your team. Confirm its purpose before turning the clue into a registered system.

Result: a queue your team can confirm, dismiss or link.
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Inventory and sweep entry point in the test workspace.Enlarge

Inventory and sweep entry point in the test workspace.

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Where it came from is part of the answer.

An isolated signal makes your team investigate again. The sources view brings together provenance and what each connection contributed, helping distinguish a source without findings from one that needs attention.

Result: source context for the review.
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Sources and evidence view in the test workspace.Enlarge

Sources and evidence view in the test workspace.

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Keep something more useful than an alert.

When someone else picks up the work, they need the source, context and available evidence. The library brings workspace material together for review without relying on scattered conversations or the memory of the person who started the case.

Result: material available for the next review.
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Evidence library with fictional data.Enlarge

Evidence library with fictional data.

Real Fencia captures from a test workspace. Fictional data; shared views complement each feature’s specific demo.

BEFORE YOU START

Answers for your team.

Do I need to know every tool before starting?

No. Start with one supported source and review its signals. Your team can also add known systems to the register.

Do signals automatically become approved systems?

No. Detection supplies a clue. A person confirms its use and decides whether to create, link or dismiss a record.

IN YOUR TEAM’S WORKFLOW

You cannot govern what nobody has registered.

Discover brings the first clues together. Review the source, confirm the use case and turn a discovery into an owned AI system.

01

Connect the places AI appears

GitHub repositories, supported AWS and Azure resources, and authorised apps in Microsoft 365 or Google Workspace.

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Inspect the signal

See what was found and where. A dependency or an OAuth permission is a clue, not proof of actual use.

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Give it an owner

Confirm, dismiss or link the discovery to an existing system. Keep the reason with the record.

A clear scope before connecting.

Coverage depends on connected sources and permissions. Fencia does not inspect every device, browser or employee activity.

Does finding an app mean it is being used?

No. Discover distinguishes source signals from your team’s confirmation. A person checks the purpose and context before registering the system.

Start with one source and a real question.

Review how this workflow fits your team’s work with us.

Talk to Fencia