Dome historical order book snapshots

This is the product feature that turns Dome from a thin API wrapper into trading infrastructure. Native venue APIs let developers see the market now, but not replay what the book looked like minute by minute or second by second in the past. That missing history matters for backtesting, slippage modeling, market making, and proving whether a strategy would actually have filled, rather than just looked good on last trade prices.

• Polymarket exposes live order book and market data through public docs, and Kalshi says its API provides current order books and market data. The gap is historical depth. Dome fills that by storing snapshots over time, then serving them in a consistent format across venues.
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• That makes Dome useful to a different customer than a casual app builder. Smaller quant shops, market makers, and analytics products need to reconstruct spreads, depth, and queue position over time. A price chart alone cannot show whether size was actually available when a bot would have traded.
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• The closest analogue is crypto market data infrastructure. Exchanges expose execution and top of book data, while specialized vendors win by warehousing full market history for research and execution tooling. In prediction markets, Dome is building that picks and shovels layer before native platforms have made it a standard product.
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As prediction markets shift from retail novelty toward professional trading workflows, historical book data becomes table stakes. The companies that own the cleanest replayable market history will be best positioned to power backtesting systems, smart order routers, and eventually the default execution layer that sits in front of fragmented venues.