
What happened
Sequoia led Catalyst's $30 million seed round, joined by Jump Trading, PeakXV, Lux Capital, AntiFund, Coinbase, and Premji Invest. Catalyst's agents convert natural language into trading strategies and execute them, with a human required to accept.
Why it matters
The startup says its pilot generated hundreds of millions in trading volume over a couple of weeks. Users are now being let off Catalyst's waitlist, and the product is expected to be widely available in time.
WHO IT HITSRetail investors who want to act on an investing thesis without building the trade themselves are the target, and the company says its user education tools are meant to explain safety and risks. Whether regulators or platforms treat agent-executed retail trades differently remains to be seen.
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Catalyst's founders, Justin Zheng and Dylan Iskandar, met as teenagers over a 2019 poker game at a conference run by economist Tyler Cowen, and both arrived with unusually technical résumés: Zheng worked on a Village Global-backed biometrics startup and later joined Sam Altman's Worldcoin, while Iskandar published cybersecurity papers for the U.S. Department of Defense in high school. They cofounded Catalyst in 2025 around a single question — how to make an increasingly complex financial world navigable for everyone.
The pitch arrives at a moment when, as the founders put it, new financial assets have exploded in number and no single human can map the optimal path, while prediction markets and crypto have become more normalized. That combination cuts both ways for a trading-agent startup: it explains the demand, and it explains why misuse is a live concern the company is trying to get ahead of with education tools. Sequoia partner George Robson frames the agents as "a suit of armor as you navigate the financial world," aimed at moving everyday traders up the sophistication curve.
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