Catalyst, a San Francisco-based AI fintech startup, has raised $30 million in Series A funding led by Sequoia Capital to develop AI-powered trading tools for retail investors.
The funding round included participation from SF1, Selini Capital, Jump Trading, Peak XV Partners, Lux Capital, AntiFund, Coinbase Ventures and Premji Invest.
Catalyst plans to use the new capital to expand its quantitative engineering, reinforcement learning and data science teams. The company will also accelerate the development of its multi-exchange API infrastructure to connect its platform with more trading venues.
Founded by Justin Zheng and Dylan Iskandar in 2025, Catalyst is building AI agents that help users develop, test and execute trading strategies. The platform aims to make complex financial markets easier to navigate by allowing users to describe their investment ideas in natural language.
How Catalyst Uses AI to Automate Trading
Catalyst is developing an AI-powered trading platform designed to help retail investors manage increasingly complex financial markets.
Its AI agents analyze multiple sources of information, including financial news, real-time order books, social sentiment and historical macroeconomic data. The system uses this information to help users develop trading strategies and assess potential market opportunities.
Users can describe their trading objectives in everyday language. Catalyst’s agents then work to translate those instructions into trading strategies, test them against historical data and prepare them for execution.
The platform is also designed to manage position sizes, identify hedging opportunities and apply stop-loss settings within risk limits established by users.
By connecting to brokerage accounts and digital asset exchanges through APIs, Catalyst aims to bring strategy development and trade execution into a single workspace. Users must approve their strategies before execution, according to the company’s description of its approach.
Sequoia Capital Backs Catalyst’s AI Fintech Vision
The $30 million funding round brings together investors from venture capital, cryptocurrency and financial trading.
Sequoia Capital led the round, with participation from Jump Trading, Peak XV Partners, Lux Capital, AntiFund, Coinbase Ventures, Premji Invest, SF1 and Selini Capital.
The investment will help Catalyst expand its technical team and build infrastructure to support integrations across multiple exchanges.
The company is targeting a financial market where investors have access to an increasing number of assets, trading platforms and data sources. Catalyst believes AI agents can help users process this information and turn their investment ideas into structured strategies.
Young Founders With Backgrounds in AI and Technology
Catalyst was founded by Justin Zheng and Dylan Iskandar, who bring experience in technology, cybersecurity and digital assets.
Zheng developed an interest in Ethereum at an early age and later built a biometrics startup backed by Village Global. He also worked with Worldcoin.
Iskandar developed expertise in cybersecurity while still in school and contributed to research associated with the U.S. Department of Defense.
The founders met as teenagers in 2019 and stayed in contact before deciding to build a company together. They launched Catalyst in 2025 with the goal of making sophisticated financial tools more accessible to individual investors.
The founders believe AI can help people understand financial markets and manage strategies that would otherwise require significant technical knowledge.
Catalyst Aims to Make Advanced Trading Tools More Accessible
Professional trading firms have traditionally relied on teams of quantitative researchers, engineers and analysts to develop complex trading strategies.
Catalyst wants to bring some of these capabilities to retail investors through AI agents that can research market information, test strategies and help execute trades.
George Robson, a partner at Sequoia Capital, described the platform as a way to help users explore investment ideas, identify suitable financial instruments, manage costs and prepare trades around specific market events.
Catalyst has also reported that an early pilot generated hundreds of millions of dollars in trading volume over a period of a few weeks. The company has not provided further details in the supplied information about the pilot’s methodology or the number of participants.
Risk Management Remains a Key Challenge
Although AI trading tools could make financial markets easier to navigate, automated trading also carries risks. Market volatility, inaccurate predictions, technical failures and poorly designed strategies can lead to losses.
Catalyst says it wants to build a platform focused on responsible investing rather than gambling. The company plans to develop educational tools that explain financial risks and help users understand how their strategies work.
Its approach includes user-defined risk parameters and human approval before trade execution. However, these safeguards cannot eliminate the possibility of losses.
With $30 million in new funding, Catalyst plans to expand its engineering capabilities and strengthen its trading infrastructure as it works to bring AI-powered financial tools to a wider audience.
The company’s long-term goal is to make advanced trading technology accessible beyond professional investors and hedge funds, while helping users better understand the risks involved in financial markets.
