Totalis

Totalis is a derivatives layer for prediction markets that lets traders combine two to five event outcomes across politics, crypto, stocks, sports, weather, and macro into a single parlay trade. Instead of placing separate bets on each market, users stake one position on a combined thesis (for example, Google shipping the top AI model and the S&P closing above a target) and receive a larger payout only if every leg resolves in their favor. The launch matters because prediction markets have grown quickly but still mostly resemble single-event betting, and Totalis is pitching parlays as the first structured primitive on top of that liquidity, with more complex structured products planned next. Under the hood, Totalis skips orderbooks and routes each multi-leg ticket through an RFQ flow where market makers return a quote that the user can accept or reject, which is designed to make capital use more efficient when a trader's real view is about correlated events happening together. The team is starting with fast-resolving, data-rich, recurring markets where correlations are easier to price, and the product is currently restricted to users outside the United States for regulatory reasons. Totalis is built by Eric Liu and Pravesh Mansharamani in San Francisco and is part of Y Combinator's Spring 2026 batch . For founders and investors tracking the prediction market stack, the launch is worth a look as an early attempt to move the category beyond single-market wagers toward the kind of baskets, spreads, and hedges that already exist in mature financial markets.