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Catalyst

Category: AI in Fintech

AI trading-agent platform that turns a retail investor's plain-language thesis into a researched, backtested, and executed trading strategy, with the user approving the final trades. Catalyst was founded in 2025. The company is led by Justin Zheng. Based in United States. Total funding raised: $30M. Latest round: Seed. Key investors include Sequoia Capital, Jump Trading, Peak XV Partners, Lux Capital, AntiFund, Coinbase, Premji Invest, Selini Capital, SF1.

Founded
2025
Headquarters
United States
Total funding
$30M

Value proposition

Investors describe an intent or thesis in natural language. Catalyst agents then gather market signals, build the strategy, choose assets, optimize costs and execute across venues. This removes the need to understand market plumbing, and safety limits plus human approval stay in place.

Products and solutions

Catalyst app (research preview, waitlist rollout): natural-language strategy builder, visual workflows that link signals, conditions and trades, widgets for prediction markets, stocks, options, perpetuals, sentiment, social activity, fund flows, news and portfolio, notifications and triggers, quick trade. Supports spot tokens, perpetuals, tokenized stocks and prediction markets. Deposits accepted via fiat (Apple Pay, credit card) or crypto (USDC, SOL, ETH, BNB).

Unique value

An 'intent layer for all of finance': state what you believe, and agents research, strategize, monitor events and execute end-to-end. The platform is non-custodial and uses a verifiable execution framework with user-set budgets and controls.

Target customer

Retail and everyday investors. The pilot focused on power traders and high-frequency retail traders.

Industries served

Retail investing / brokerage, crypto and onchain trading, prediction markets, fintech

Technology advantage

Custom agent execution framework with strict controls over data access, strategy construction and order placement. The design is non-custodial and every action is verifiable end-to-end. It orchestrates across multiple venues and asset classes, including onchain and offchain assets and prediction markets. The team has backgrounds at Palantir, Scale AI, Citadel, Citadel Securities, Hudson River Trading and Jump Trading.

How they differentiate

The product starts from user intent rather than from the brokerage UI. A single agentic workflow combines research, strategy, backtesting and execution across stocks, crypto perpetuals, tokenized assets and prediction markets. A human-in-the-loop approval step and a non-custodial design address safety concerns, and the company stresses user education and says it is 'not a casino'.

Main competitors

Scalar Field (agentic trading desk), Robinhood (retail brokerage adding AI features), Composer (no-code / AI-assisted trading strategies)

Key partnerships

Strategic investors Coinbase and Jump Trading (no product integration announced), Wilson Sonsini served as legal counsel on the seed round

Major milestones

2025: founded by Justin Zheng and Dylan Iskandar. Mar 2026: public launch and waitlist opened. Pilot with power traders produced hundreds of millions in volume. Oct 2026: $30M seed round led by Sequoia.

Growth metrics

The company says its pilot generated hundreds of millions of dollars in trading volume over a couple of weeks. Users are now being admitted from the waitlist. The X account had about 2.9K followers in October 2026.

Market positioning

Early-stage, heavily funded leader in agentic retail trading. Backers combine top-tier VC (Sequoia, Peak XV, Lux) with trading and crypto strategics (Jump Trading, Coinbase). The company aims to be the universal orchestration layer for turning financial ideas into trades.

Geographic focus

United States / global retail and crypto markets

About Justin Zheng

Ex-Worldcoin (Tools for Humanity), joined 2019; founded a Village Global-backed biometrics startup in high school and raised a seed round at age 16; Pioneer grant recipient for biometrics and crypto work; twice selected as the youngest IDEO CoLab fellow.

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