Polymarket versus Kalshi Access
Kurush Dubash, CEO of Dome, on unified API for prediction markets
The split between Kalshi and Polymarket is not just regulatory packaging, it determines where the data lives, how fast outside builders can read it, and who gets to build on top. Polymarket writes every trade to public blockchain rails, so developers can read raw market activity directly and reconstruct books, fills, and trader behavior. Kalshi runs as a regulated U.S. exchange on its own databases, so outside developers depend much more on the company’s APIs and internal systems for access.
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For an infrastructure company like Dome, Polymarket is the easier starting point because the chain is the source of truth. That means more historical data, more visible transaction flows, and less dependence on a single platform endpoint. Kalshi integration is slower because the underlying data is not natively public in the same way.
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The architecture also maps to different business models. Polymarket grew as a crypto native, international venue with USDC settlement and zero trading fees for liquidity growth, while Kalshi built around CFTC licensing, fiat rails, market surveillance, and a roughly 1 percent effective take rate. One is optimized for openness and scale, the other for compliance and U.S. distribution.
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Even when the markets look similar on the screen, the workflows underneath are different. On Polymarket, outside teams can inspect on chain trades and build copy trading, analytics, and routing tools from public records. On Kalshi, builders are working through an exchange style interface, where access, latency, and product depth are shaped more tightly by the platform itself.
Going forward, the winners are likely to combine both models. Kalshi is already pushing some on chain access paths, while Polymarket is moving toward more regulated U.S. infrastructure. That convergence should make the market easier to aggregate, but it also makes the data and routing layer more valuable because builders will still need one system that normalizes two very different back ends.