Turning collective belief into a tradable, real-time signal, resolved on-chain.
A prediction market allows participants to trade on the outcome of real-world events, elections, sports, economic data releases, with prices that reflect the market’s aggregated, continuously updated probability estimate. Resolution happens on-chain, typically anchored to an oracle or a decentralized dispute mechanism, so no single party controls the final outcome.
The category has scaled rapidly. Monthly prediction market volume reached $25.7 billion in March 2026, with January 2026 setting an all-time high of $26.75 billion in notional volume. Kalshi alone processed $23.8 billion in trades across 2025, growth of more than 1,100% year over year, and has drawn integrations from major platforms including Robinhood, Coinbase, and Google Finance.
Market figures are drawn from public reporting current as of early-to-mid 2026 (sources include DefiLlama, CoinGecko, The Block, Dune Analytics, Gartner, and industry market-research reports). These move quickly, verify and refresh before relying on them.
The hardest technical problem in this category isn’t the trading interface, it’s the resolution layer: accurately and verifiably settling markets against real-world outcomes, at scale, without introducing a point of manipulation. Increasingly, that resolution layer is being paired with AI models that help calibrate odds in real time and flag mispriced contracts before human traders do.
Recent election and macroeconomic event cycles demonstrated that prediction markets can outpace traditional polling in accuracy, and do it continuously rather than periodically. Combined with AI-driven market creation and calibration, we see this as one of the categories with the most room left to run, and one where technical depth in both the AI layer and the settlement layer determines who leads it.
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