Unified APIs Power Institutional Prediction Markets

Institutional interest means prediction markets are starting to behave less like novelty consumer apps and more like real trading venues. Traders and market makers care about one thing, whether they can pull clean data fast enough to price contracts, hedge risk, and update quotes across venues. That makes Dome useful not just for people building apps, but for firms running backtests, automated strategies, and pricing systems on top of fragmented market infrastructure.

• Kalshi already treats liquidity providers like exchange infrastructure, with retail paying roughly 1 percent on volume while market makers can trade free and earn rebates for posting bids and offers. That creates a professional user class that needs data feeds and execution tools, not just a consumer interface.
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• Polymarket has followed the same path from the crypto side, using maker incentives and liquidity provider fees to keep markets tight, while adding selective taker fees in early 2026. When venues start paying for tighter spreads, firms with trading systems show up quickly.
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• Dome sits in the middle of a market that is splitting into builders and operators. The interview points to roughly 75 percent builder usage and 25 percent trader or market maker usage, with institutions using the product for backtesting, analytics, high frequency trading, and pricing sweepstakes style products.
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The next step is a market structure shift, where prediction market APIs start to look more like exchange data plumbing. As volume concentrates in sports, politics, and niche local markets, the winners will be the infrastructure companies that can serve both app developers and professional trading firms from the same normalized data layer.