Catalyst, a startup building AI trading agents for retail investors, has raised a $30 million seed round led by Sequoia Capital. Other backers in the round include Jump Trading, PeakXV, Lux Capital, AntiFund, Coinbase, and Premji Invest. The company was founded in 2025 by Justin Zheng, 25, and Dylan Iskandar, 21. Zheng previously joined Sam Altman’s Worldcoin, while Iskandar drew attention earlier in life for publishing a cybersecurity paper for the U.S. Department of Defense while still in high school.
Catalyst says its main goal is to help ordinary users handle an increasingly complex financial market. Its product turns natural-language prompts into trading strategies and can execute them, though trades still require human confirmation at this stage. The startup’s longer-term vision is a workflow in which users only state their intent and the agent completes the trade from end to end. The funding round signals early investor backing for tools designed to lower the barrier to participation in advanced trading systems.
AI trading agent startup Catalyst, which is focused on retail traders, has raised a $30 million seed round led by Sequoia Capital, according to BlockBeats on Oct. 8.
Investors in the round also include Jump Trading, PeakXV, Lux Capital, AntiFund, Coinbase, and Premji Invest.
Founded in 2025 by Justin Zheng and Dylan Iskandar
Catalyst was founded in 2025 by Justin Zheng, 25, and Dylan Iskandar, 21. The report highlighted the backgrounds of both founders. Zheng previously joined Sam Altman’s Worldcoin, while Iskandar published a cybersecurity paper for the U.S. Department of Defense when he was still in high school.
Natural-language trading is the core product idea
The company’s stated goal is to help ordinary people handle an increasingly complex financial world. Catalyst’s agent can translate natural-language input into trading strategies and execute them.
At the moment, trades still require human confirmation. Its eventual vision is for users to simply express their intent, with the agent carrying out the transaction flow end to end.
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