What we actually run
- Fleet management and modernization — provisioning, patching, lifecycle management, standardization
- Application and extension visibility — including the browser extensions and background AI integrations a standard software inventory misses
- Policy enforcement that's practical, not theoretical — device-level controls that reflect your actual AI data-handling policy
- Signal routing into governance — endpoint telemetry flows into the same operational loop as service desk and NOC signal
Why this matters more than it used to
The average enterprise employee now uses roughly 14 AI tools, while IT is typically aware of only 4 to 5 of them. Endpoints are the earliest, most reliable place that gap actually closes — because AI tools mostly arrive as a browser extension or desktop app before anyone files a ticket.
What you get
- A modernized, well-managed fleet without the operational overhead landing on your internal team
- Real visibility into what's installed and running — including the AI tools nobody formally requested
- Endpoint signal that feeds directly into AI governance and service desk operations
- Fewer surprises, because the earliest indicator of shadow AI usage is being watched, not ignored