Tanium teams with NVIDIA to manage local AI endpoints

Tanium has announced a collaboration with NVIDIA to extend its endpoint management tools to NVIDIA local AI infrastructure. The arrangement covers several NVIDIA systems designed for AI use on deskside and desktop machines.

The move applies to RTX Spark, DGX Spark, DGX Station and DGX Station for Windows, bringing those machines under the same management framework Tanium uses for other enterprise endpoints.

As more AI workloads move from centralised infrastructure to local devices, companies are starting to deploy systems outside the Windows and x86 environments many IT management products were originally built to handle. DGX Spark runs on NVIDIA DGX OS, an Ubuntu-based Linux distribution intended for AI workloads.

Tanium said its platform has been validated on NVIDIA DGX OS and can provide patching, asset inventory, configuration compliance and process management without requiring a custom build. Support is already in place for DGX Spark and RTX Spark, while support for DGX Station and DGX Station for Windows is being expanded.

Its software is also listed in NVIDIA's DGX Spark Enterprise Lifecycle Integration Guide. Tanium described itself as among the first endpoint management platforms able to govern on-device AI agents at deployment and during runtime.

Management scope

According to the companies, IT and security teams using the combined setup will be able to view inventory, running processes, patch status and compliance across fleets of AI-focused machines. Tanium said the system can also provide visibility into CPU, memory, GPU and temperature data across a fleet.

The functions outlined include fleet-level consumption monitoring, giving operators a real-time view of which models are running and how much compute and memory they are using. They also include runtime controls intended to let IT and security teams start, monitor and stop AI agents automatically if defined time or resource thresholds are exceeded.

Tanium said organisations can deploy AI agents across fleets as packages or processes using its Deploy product. It added that its architecture is designed to scale from smaller estates to fleets running into the thousands of units.

Other features cited include compliance reporting mapped to CIS and NIST frameworks, software bill of materials tracking across system packages, containers and language runtimes, and privileged access with session recording. The system can also be deployed in air-gapped environments.

Harman Kaur, Chief Technology Officer at Tanium, said the spread of AI hardware into the workplace has created a new management challenge for IT and security teams.

"NVIDIA's vision for AI compute is bringing a new class of endpoint into the enterprise, including new hardware architectures, new operating systems, and AI agents running locally on all of them," said Harman Kaur, Chief Technology Officer at Tanium.

"To manage that infrastructure with confidence, IT and security operators need real-time visibility and control across their entire fleet. Tanium extends that capability to NVIDIA's AI endpoints the same way we have extended it everywhere else. With attacks now moving at machine speed, there's no room for blind spots," Kaur said.

Broader shift

The collaboration reflects a wider shift in enterprise computing as AI models and tools move closer to end users rather than remaining solely in data centres. That creates operational issues for businesses that need to manage a mixed estate of conventional PCs, servers and newer AI-focused devices under common security and compliance rules.

NVIDIA said the partnership is intended to help businesses fold its local AI systems into existing IT processes rather than manage them as a separate category of hardware.

"NVIDIA DGX and RTX platforms bring powerful local AI to enterprise developers and employees, enabling them to build and run AI within their established workflows," said Chris Marriott, Vice President of Enterprise Platforms at NVIDIA.

"Our collaboration with Tanium extends that integration to IT operations, helping organizations incorporate these platforms into fleet management processes they already use as they deploy AI compute at scale," Marriott said.