Uploaded May 2026 | Updated September 2026, 1 week ago
How do you build enterprise AI fast without compromising data control?
In this case study, Red Hat and HP showcase how teams can prototype and run AI locally using the HP ZGX Nano AI Station. Led by Red Hat CTO Vincent Caldeira, the team developed a sovereign AI agent for anti-money laundering (AML) built entirely on a desktop environment.
By enabling rapid prototyping, local testing, and full data control, ZGX Nano helps teams:
- Accelerate build–test–debug cycles
- Maintain governance in regulated environments
- Reduce dependency on cloud infrastructure
The result: faster innovation, improved developer productivity, and real-world AI solutions built with confidence.
Build locally. Iterate faster. Scale confidently.
How do you build enterprise AI fast without compromising data control?
In this case study, Red Hat and HP showcase how teams can prototype and run AI locally using the HP ZGX Nano AI Station. Led by Red Hat CTO Vincent Caldeira, the team developed a sovereign AI agent for anti-money laundering (AML) built entirely on a desktop environment.
By enabling rapid prototyping, local testing, and full data control, ZGX Nano helps teams:
- Accelerate build–test–debug cycles
- Maintain governance in regulated environments
- Reduce dependency on cloud infrastructure
The result: faster innovation, improved developer productivity, and real-world AI solutions built with confidence.
Build locally. Iterate faster. Scale confidently.
