AI Startup Catalyst Raises $30m In Series A Round Led By Sequoia
Catalyst, a San Francisco-based artificial intelligence startup developing automated trading tools for retail investors, has raised $30 million in a Series A funding round led by Sequoia Capital.
The round also drew participation from SF1, Selini Capital, Jump Trading, Peak XV Partners, Lux Capital, AntiFund, Coinbase Ventures, and Premji Invest.
Catalyst said it would use the proceeds to expand its quantitative engineering, reinforcement learning, and data science teams, while accelerating the development of its trading platform’s application programming interfaces (APIs) for integration with multiple exchanges.
Founded by Justin Zheng, Catalyst develops a cloud-based platform that uses autonomous AI agents to design and execute trading strategies across financial markets.
Its software combines financial news, live order-book data, social sentiment and historical macroeconomic information to inform trading decisions, according to the company.
The platform connects to users’ existing brokerage and digital asset exchange accounts through cryptographic API keys.
Its agents can develop and backtest trading strategies, adjust position sizes, manage hedging and establish stop-loss mechanisms within risk parameters set by users.
The approach aims to bring quantitative trading capabilities, traditionally associated with professional trading firms and institutional investors, to individual investors through an automated software interface.
Reinforcement learning models are used to process changing market conditions and inform the platform’s trading decisions.
Catalyst’s planned investment in multi-exchange API integrations will support connectivity across trading venues, while additional engineering and data science hires will help develop its models and execution capabilities.
The funding comes as financial technology companies explore the use of generative AI and autonomous agents in investment research, market analysis and trade execution.
However, automated trading systems remain exposed to market volatility, liquidity constraints and model errors, while access to brokerage accounts and execution permissions introduces additional security and risk-management considerations.
Catalyst’s platform allows users to set risk parameters governing the agents’ activities.
The company did not disclose its valuation following the funding round or provide details on assets traded through the platform.
