AI-driven
Ahuora is an investment management firm that uses AI to identify and trade on investment opportunities
AI for Investing
A set of AI models take diverse quantitative and qualitative inputs and produce recommendations.
Learn MoreAlignment of interest
The portfolio manager is the largest investor in the fund, holding the majority of its value.
Learn MoreOur Company
Founded in 2017 by two pioneering scientists, Ahuora harnesses the power of AI and customer research to transform stock trading.
- Based in Cupertino, CA
- Scientist Founders
Ahuora is
Our Leaders

Sia Gholami
Sia Gholami is a distinguished expert in the intersection of
artificial intelligence and finance. He holds a bachelor's, master's, and Ph.D. in computer
science, with his doctoral thesis focused on efficient large language models and their
applications—an area crucial to the development of advanced AI systems. Specializing in machine
learning and artificial intelligence, Sia has authored several research papers published in
peer-reviewed venues, establishing his authority in both academic and professional circles.
Sia has created AI models and systems specifically designed to identify opportunities in the
public market, leveraging his expertise to develop cutting-edge financial technologies. His most
recent role was at Amazon, where he worked within Amazon Ads, developing and deploying AI and
machine learning models to production with remarkable success. This experience, combined with
his deep technical knowledge and understanding of financial systems, positions Sia as a leading
figure in AI-driven financial technologies. His extensive background has also led him to found
and lead successful ventures, driving innovation at the convergence of AI and finance.

Saba Khashe
Saba Khashe is a highly accomplished researcher and expert in
designing systems for AI-driven hedge funds. She holds a bachelor's degree, two master's
degrees, and a Ph.D. from the University of Southern California, where she specialized in
Human-Computer Interaction. Saba has authored several high-impact research papers published in
peer-reviewed venues, showcasing her expertise in integrating human-in-the-loop systems. Her
work focuses on incorporating both qualitative and quantitative measures into AI systems,
ensuring that these technologies are advanced, practical, and user-centered.
In her most recent role at Atlassian, Saba is dedicated to developing products that create
significant value for all stakeholders, further solidifying her reputation as a leader in the
field. Her unique combination of skills makes her a key figure in optimizing AI-driven financial
systems.

Ehsan Roosta
Ehsan Roosta has worked in both the technology and financial industries. Most recently, he has been managing private clients' assets, investing in financial markets, real estate, and private opportunities. Prior to his work in investment management, Ehsan covered Consumer & Retail companies at Wells Fargo Investment Banking and Capital Markets Group. At Wells Fargo, he was responsible for various capital markets and M&A transactions. In the technology sector, Ehsan was an early design engineer at the high-tech startup ClariPhy Communications (later acquired by Inphi). He earned a master's degree in electrical engineering from the University of Southern California and an MBA from the University of Chicago Booth School of Business, with a focus on Accounting, Economics, and Finance.
Our Funds
AhuoraXP is an investment fund that merges advanced AI and machine learning with human expertise to create superior investment strategies. By leveraging sophisticated technologies, AhuoraXP analyzes extensive datasets to identify market opportunities and generate high-confidence investment recommendations, which are then validated by experienced portfolio managers.
AhuoraAT is an investment fund that uses machine learning autonomously analyzes vast amounts of market data to identify optimal buy and sell opportunities without human intervention. These algorithms execute trades in real-time, leveraging AI's predictive capabilities to maximize returns and manage risks effectively.
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