DeFi Startup Gondor Secures $2.5M to Bring Lending and Leverage to Prediction Markets
DeFi startup Gondor has raised $2.5 million in a pre-seed round to bring borrowing and leverage to on-chain prediction markets, opening a public beta that could change how capital moves through Polymarket and similar platforms.
The December 2025 round included Prelude, Castle Island Ventures and Maven11, along with continued backing from investors tied to the Polymarket ecosystem. Gondor’s goal is to become the core lending layer for prediction markets, not just another place to trade.
Today, most prediction markets lock capital until an event settles. Once traders buy “Yes” or “No” shares, their money is stuck for weeks or months and can’t be reused or posted as collateral. Gondor aims to unlock that idle capital by letting users deposit active Polymarket positions and borrow USDC stablecoins against them, while keeping their original exposure.
With its beta, Gondor is also rolling out up to 2x leverage via a simple looping strategy. Traders can borrow against their positions and put that capital back into new trades, effectively doubling size without adding fresh funds. The team has hinted at raising leverage to 4x–5x in 2026 once liquidity and risk systems prove themselves on-chain.
Gondor’s bigger vision is to turn prediction markets into a real on-chain asset class. Ethereum cofounder Vitalik Buterin has argued that prediction markets are unattractive for hedging because they don’t generate yield. Gondor doesn’t pay yield directly, but it introduces the building blocks for future products: collateral, lending, leverage and structured strategies.
The project casts itself as the Aave of prediction markets, sitting on top of Polymarket rather than competing with it. That also brings new risk. Leveraged positions can be liquidated in thin, fast-moving markets, potentially triggering cascades. Gondor is starting cautiously with conservative borrowing limits and only high-liquidity markets in beta, making it one of the most closely watched experiments in the prediction market space.