BiyaPay Analyst: Following Circle, the US Stock Market Will See Another Major IPO, Silicon Valley's "Design Tool" Figma Takes the Capital Stage

By: theblockbeats.news|2025/07/31 11:32:20

BlockBeats News, July 31st, Cloud-based collaborative design platform Figma (ticker: FIG) officially landed on the NYSE on Wednesday Eastern Time, with an IPO price of $33 per share, higher than the original target range. The IPO was oversubscribed by 30 times, raising over $1.2 billion. Post-dilution valuation reached $19.5 billion, making it one of the most anticipated U.S. stock IPOs this year.

Previously, Figma was planned to be acquired by Adobe for $20 billion, but the deal fell through due to antitrust scrutiny. Now, leveraging its strong profit-making ability and 13 million monthly active users worldwide, the company has independently stepped onto the capital stage. In the fiscal year 2024, the company's revenue reached $7.49 billion, a 48% year-on-year growth, achieving profitability and entering the "SaaS Profitability Club."

Figma's successful listing has also injected confidence into U.S. tech stocks, indicating that the IPO market recovery is accelerating. The current market is in a key window for the repricing of AI, collaboration tools, and design software.

Through BiyaPay, investors can directly trade popular U.S. new stocks like Figma and Hong Kong stock assets using USDT, without the need to open an offshore account. With fast fund transfers and convenient operations, investors can easily participate in global high-quality IPO opportunities and grasp the trend of integration between the crypto and traditional financial markets.

In early 2026, AI has returned to the center of the crypto market — not as a short-lived narrative, but as part of trading infrastructure. AI-powered tokens continue to attract attention, while AI-assisted trading tools are increasingly embedded into exchanges, strategy platforms, and risk systems. For traders, the key question is no longer whether AI will be used, but how it changes execution, risk control, and decision-making in practice. Understanding this shift requires separating market narratives from the actual mechanics of AI-driven trading.

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