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🔥BTC/USDT

Catalyst raises $30 million for AI trading agents

2026-10-10 08:07

Catalyst has raised $30 million in a seed round led by Sequoia Capital, placing AI-driven trading automation at the center of a new group of crypto products competing for retail users before their public launches. Jump Trading, PeakXV, Lux Capital, AntiFund, Coinbase, and Premji Invest also participated in the financing, which Catalyst announced on Oct. 8.

Founded in 2025, Catalyst is building a platform where users can describe a trading idea in natural language rather than assemble a strategy through charts, code, or multiple trading interfaces. Its AI agents are designed to research relevant inputs, construct a strategy, run historical backtests, monitor market signals, and prepare trades for user approval.

The approval step is central to Catalyst’s proposed workflow. The platform says its agents will not execute a trade without the user signing off, placing the product closer to assisted automation than a fully autonomous portfolio manager. That design could appeal to users who want automated strategy development and monitoring while retaining control over final execution.

Access is currently limited to a waitlist at catalyst.app. Applicants select “Join waitlist” and provide an email address and X account. Catalyst describes retail participants as its intended audience, framing the service as a way to move from an initial market idea to an executable order through one automated process.

Catalyst targets the gap between trade ideas and execution

The seed round gives Catalyst substantial early backing for a product category that remains difficult to deliver reliably. Generating a strategy from a written prompt is only one part of the task; a useful system must also handle market data, define risk parameters, test assumptions against historical conditions, and translate the resulting plan into orders without creating a false sense of certainty.

Historical backtesting, which tests a strategy against past market data, can help users identify how an approach would have performed in earlier conditions. It cannot establish that the same strategy will succeed in live markets, where liquidity, volatility, transaction costs, and sudden news events can differ sharply from the historical period.

Catalyst’s approach reflects a growing product focus on simplifying complex trading workflows rather than requiring users to navigate separate research, analytics, and execution tools. The model could reduce the technical burden of turning an idea into a structured trading plan, though users would still need to judge whether an agent’s assumptions, inputs, and suggested risk limits are appropriate.

The presence of Jump Trading in the round also connects Catalyst with a firm known for quantitative trading and market infrastructure, while Sequoia Capital’s lead role signals that venture firms see a potentially large consumer-facing market for AI-native financial tools. The announcement did not provide a valuation, launch date, or details on which venues and assets Catalyst will support.

RocX uses testnet activity to distribute points

RocX, another early-stage project, launched its testnet on Oct. 5 with a different model: rewarding user participation through a framework it calls Proof of Activity, or PoA. The project says it links on-chain fund movements with logged user actions under the phrase, “Every Web3 Activity Creates Value.”

The RocX testnet is built on Base Sepolia, a test network where tokens have no intended real-world value. Users can obtain Base Sepolia test ETH through Alchemy’s faucet, connect a wallet through rocx-testnet.com, and bind an X account under the app’s “My Page” section.

RocX also offers daily check-ins in an “Explore” section, with the interface listing 100 points for each check-in. A separate “DeFi” section allows users to deposit testnet ETH. The points structure combines recurring social activity with a wallet-based action, creating a visible record of engagement inside the test environment.

That structure gives RocX a way to measure participation before a mainnet launch, although the project has not stated whether testnet points will translate into tokens, governance rights, preferential access, or any future financial benefit. Testnet campaigns frequently use points to encourage product testing and identify active users, but the eventual treatment of those points depends on the project’s later decisions.

SmartX opens a second waitlist round

SmartX is taking a more social route into the trading market. The app describes itself as a personalized social trading product covering meme tokens, perpetual contracts, stocks, and prediction markets. On Oct. 8, it said the second round of its waitlist had opened.

Applicants begin at smartx.io, select “Waitlist,” and complete a six-question test before submitting an email address and verification code. SmartX ranks applicants based on when they joined and a metric called “Boost.” Users can increase Boost by inviting friends; when two users have the same Boost level, the earlier applicant ranks higher.

The company was among 24 early-stage businesses selected for YZi Labs’ EASY Residency Season 4 cohort, announced on Aug. 25. YZi Labs allocated $500,000 to each company in the cohort, including SmartX, implying a $12 million commitment across the 24 selected firms.

SmartX’s waitlist design turns access into a referral-driven ranking system, while RocX rewards repeated testnet use and Catalyst is gathering users for an AI-assisted trading platform. Together, the three launches show how early crypto products are combining automation, social identity, and measured user activity well before broad public availability.

For users, the immediate practical distinction is straightforward: Catalyst is collecting early demand for an AI trading workflow, RocX is running an activity-based testnet, and SmartX is using a ranked waitlist for a social trading application. None of the three processes guarantees future access, token distributions, or returns, but each provides its developers with an early pool of users whose behavior can shape the eventual product.


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