SAN FRANCISCO, Sept 18 — ASUS and Poesis today announced the results of a week-long experiment that successfully deployed agentic AI to trade autonomously in financial markets. The system ran entirely on the ASUS ExpertCenter Pro ET900N G3, a deskside supercomputer built on the NVIDIA DGX Station platform, powered by NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip.
Throughout the test, all models, agents, and workflows ran locally on the ASUS ExpertCenter, showing that agents can function in live markets without relying on cloud-based AI infrastructure.
“While this was an early-stage experiment, it showed that agents can operate continuously in live markets while remaining within clearly defined constraints,” said Alex Popa, Founder and CEO of Poesis, an AI-native asset manager developing agentic systems for financial markets.
The collaboration reflects growing interest across industries in moving agentic AI from experimentation towards practical development, particularly in asset management.
“Working alongside Poesis at the intersection of AI and financial markets gave us valuable insights,” said Yen Hoang, Director of Marketing, B2B, ASUS North America. “As agentic AI continues to evolve, projects like this are essential to helping us better understand how autonomous investment workflows can be developed and deployed in real-world trading environments.”
Built on NVIDIA DGX Station Powered by NVIDIA Blackwell Ultra
The week-long experiment ran on the ASUS ExpertCenter Pro ET900N G3, powered by NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip. Featuring up to 20 petaFlops of AI performance and 748GB of coherent memory, the system enabled Poesis to deploy a multi-agent AI workflow locally on a single machine.
Using live capital, the agents autonomously handled investment research, risk management, and trade execution while operating within predefined mandates.
