Trading bot developers lack staging environments that faithfully reproduce exchange-side behavior including partial fills, timing collisions, and fee settlement edge cases. This forces production to serve as the only true test environment, creating dangerous gaps between unit-test coverage and real trading outcomes. Existing mock frameworks do not model exchange non-determinism accurately enough to catch failure modes before capital is at risk.

Trading bot developers are forced to test with real capital because no mock environment faithfully reproduces exchange non-determinism like partial fills, timing collisions, latency spikes, and fee edge cases.

Crypto and equities algo-trading teams (2-50 person shops) and solo quant developers deploying automated trading agents to CEXs and DEXs.

Teams already pay $5K-50K/mo for market data, co-location, and backtesting infra — a staging environment that prevents even one blown trade pays for itself instantly; the pain is acute because every production bug is denominated in dollars lost.

MVP replays real historical order book data through a simulation engine with configurable non-determinism (partial fill probability distributions, latency jitter, fee model plugins) exposed via exchange-compatible REST/WebSocket APIs so bots connect without code changes; start with Binance and Coinbase API compatibility.

~$2B addressable across algo-trading infra tooling — tens of thousands of crypto trading firms plus growing AI agent trading ecosystem, with expansion into TradFi prop desks.