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Beginning with the US presidential elections in November 2024, when prediction markets catapulted into mainstream culture, their rise has been undeniable. Kalshi and Polymarket have seen their valuations balloon to $40 billion and $21 billion, respectively, and the majority of the top US bookmakers have scrambled to expand into the prediction space in various forms, either by building their own exchanges, acquiring existing ones or engaging in market-making.

Commercial sports betting generated just under $17 billion in nationwide revenue in 2025, which is why Davenport asserts that the “stakes of this case are exceptionally high”. Kalshi and Polymarket alone posted more than $45 billion in trading volume, which is similar but not identical to betting revenue, in August. That was a 15% decline from July, although that drop is attributed to the conclusion of the Fifa World Cup tournament that month per Yahoo! Finance.

The American Gaming Association estimates that the exchanges have siphoned more than $1.3 billion in would-be tax revenue from states. One of the AGA’s primary spokespeople pin its fight against prediction markets is former New Jersey governor Chris Christie, who championed the PASPA case to the Supreme Court.

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Genius signed deals with both Polymarket and Kalshi in August, to provide real-time event data and league integrity services, as well as streaming services. Fellow data provider Sportradar also announced similar multi-year partnerships with both Kalshi and Polymarket in June. 

Initial reaction from investors was largely unfavourable. Genius shares plunged 13% on 18 Sept., falling 17% for the week. The data provider closed the session at $5.64 per share, well below the $6.19 price when it announced the Legend acquisition in February.

The launch of Prediction.com comes amid a strategic integration phase following Genius Sports’ acquisition of Legend. 

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Cubeia is currently heavily reliant on Claude, and Grenstad questions what could happen if AI providers raise prices or if quality changes. For now, however, Grenstad sees the uncertainty as something Cubeia can learn to manage.

“We’re confident that the question marks will be solved as we work through them. We’ll see the problems, learn how to manage them, and adapt.”

When Cubeia began their AI-journey, the objective was simple.