Tradeweb reported a 9% rise in second-quarter revenue to $558.9 million as average daily volume reached a quarterly record of $3.01 trillion.
Beyond the financial results, CEO Billy Hult used the earnings release to place the company's Kalshi partnership alongside artificial intelligence and tokenisation as technologies shaping the next phase of institutional electronic trading.
Tradeweb now presents prediction-market data as part of the same long-term technology strategy as AI-powered execution tools, generative AI research and tokenised market infrastructure.
Kalshi Data Moves into Institutional Workflows
The Kalshi initiative goes beyond displaying a standalone market feed. Tradeweb has integrated real-time event probabilities and a dedicated pricing index into workflows that institutional clients already use for market data, pricing and risk analysis.
Clients can view probabilities linked to political, economic and financial outcomes alongside rates, credit and equity data without leaving Tradeweb. The phase described in the results centres on data rather than execution in event contracts. It does not establish prediction markets as an institutional asset class, but embeds their pricing signals in established market infrastructure.
The work builds on the first operational phase of a partnership announced earlier in 2026. That rollout introduced a dedicated Kalshi data suite, with support also announced for the American Power Index, which combines probabilities linked to control of the US presidency, House and Senate.
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Talos has taken a different route by allowing market makers and trading firms to access Kalshi through existing execution and risk-management processes. The Tradeweb and Talos integrations serve different functions, but both bring prediction-market infrastructure closer to systems already used by professional firms.
AI and Tokenisation Provide the Wider Context
Tradeweb said adoption of AiEX continued to increase as clients embedded more automation in their trading workflows. TARA applies generative AI to institutional credit data, helping users turn trading information into research and market intelligence.
In July, Tradeweb completed a real-time transaction involving tokenised US Treasuries on its platform using the Canton Network. It also participated in a DTCC initiative that processed Treasury transactions using tokenised assets held at the Depository Trust Company.
The Q2 release therefore provides a strategic frame for previously announced initiatives. By presenting Kalshi data alongside AI-driven automation and tokenised settlement infrastructure, Tradeweb is positioning prediction market information as one component of its longer-term institutional technology strategy rather than solely as a retail trading product.
