Jeremy Neely Text Jeremy

Security & Compliance · Beta

Shadow AI Scan and Reporter

Finds the AI tools in use across a client's PCs and reports the risk.

Built for: The AME Group's sales and admin teams, and client leadership

The overview of a Shadow AI discovery report with an overall risk rating (sample data).
The overview of a Shadow AI discovery report with an overall risk rating (sample data).

The problem

Employees adopt AI tools on their own, and leadership cannot see where company data is going. The vendor's stock scanner missed whole categories and kept results only in the vendor's dashboard.

What I built

I built AME's edition of the Hatz endpoint collector, a PowerShell scan pushed through N-able N-central that also keeps AME's own copy of every scan. A companion tray app files scans by client, redacts them, and builds HTML and PDF discovery reports.

How it works

  1. An admin sets up one automation object in N-central.
  2. Each PC scans browsers, desktop apps, extensions and npm packages.
  3. Hatz gets its copy; AME's copy goes to OneDrive through Power Automate.
  4. The Reporter app files scans by client and applies redaction.
  5. A report with rated observations goes out on a schedule.

Built with

  • PowerShell 5.1 / 7
  • Pester 5
  • N-able N-central
  • Power Automate
  • Python
  • SQLite

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