Institutional global long-short strategy designed to use autonomous AI agents operating under human governance
Lumenai Investments LLC today announced plans to launch the Lumenai Innovation Fund, believed to be the first institutional hedge fund built on an agentic AI architecture. The Fund is expected to begin operations on or around June 1, 2026.
The Fund is built on a fully agentic AI architecture from day one, with AI agents serving as decision-makers.”
— Javier Sanchez
In conventional quantitative funds, machine learning is embedded inside a human-directed, fixed-rules process. The Lumenai Innovation Fund inverts that structure. Autonomous AI agents are designed to originate, evaluate, and risk-manage investment ideas continuously, with human oversight focused on governance, risk supervision, and strategy. The Fund is a global equity long-short strategy with an objective of generating alpha at low beta across market regimes. These are investment objectives, not guarantees, and the Fund has no operating history.
The architecture is built in partnership with ETS Asset Management Factory, a quantitative and AI research firm developing systematic investment models since 1987.
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“Most hedge funds bolt AI onto fixed-rules systems,” said John Bailey, Founder and Managing Partner of Lumenai Investments. “We’ve inverted that. In a market where information edge has structurally collapsed, we believe the remaining edge is the adaptability of the process itself — and an agentic architecture is built for adaptation.”
“We have been applying artificial intelligence and systematic methods to financial markets for decades,” said Javier Sánchez, General Manager of ETS Asset Management Factory. “What is different about the Lumenai Innovation Fund is not that it uses AI. It is that the Fund is built on a fully agentic AI architecture from day one, with AI agents serving as decision-makers rather than as a tool inside a broader process.”
The fund is designed as a non-correlated diversifier to traditional stock and bond portfolios.
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