GIM Secures $20 Million in Series A Funding to Revolutionize Capital Markets with AI
HONG KONG, BEIJING, and SHANGHAI, July 9, 2026: Grace Investment Machine (GIM), an AI-driven investment technology firm, has successfully closed its $20 million Series A financing round. This funding, co-led by a prominent US venture capital firm and Hony Capital, alongside participation from IDG Capital and previous investor Monolith Capital, marks GIM’s third funding round in its inaugural year.
GIM aims to develop sophisticated AI systems that extend beyond mere investment research assistance. These systems, termed “Visionary Machines,” focus on generating, testing, and refining investment hypotheses using market data and feedback.
The capital markets present a dynamic environment where every hypothesis can transform into actionable insights, providing invaluable feedback that enables continuous learning and sharper judgment over time.
According to GIM’s founder and CEO, Jiahao Xu, the industry is evolving from basic information assistance to autonomous hypothesis generation and testing, with GIM leading this transformation by constructing systems that learn and improve through market interactions.
The company is progressing on two key fronts: developing foundation models tailored for capital markets and creating multi-agent systems capable of generating, validating, and evolving investment signals. Their flagship research, CogAlpha, has received an Oral recommendation at ACL 2026, showcasing a seven-layer agent architecture that translates raw data into actionable investment signals.
GIM emphasizes the concept of “Shared Prosperity,” advocating that the advancements in AI intelligence should be accessible to a wider audience rather than concentrated among a few entities. This mission resonates deeply with the investors involved in this round, who possess long-term expertise in AI and financial technologies.
In addition to its research initiatives, GIM is actively deploying AI-driven investment strategies across various asset classes, setting the stage for real-time market validation.
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