AI-Powered Trading Platform
Design a strategy, prove it against historical and simulated data.
The problem
Trading systems are unforgiving software. They run unattended, act on real money, and fail in expensive ways. The hard problem is not the trading idea but the system around it: correctness you can prove, execution you can audit, and risk controls you can trust.
The approach
Build it like safety-critical infrastructure. A single pure decision engine gives backtest-to-live parity, a durable intent-and-reconcile pipeline makes the money path auditable and restart-safe, and explicit guardrails keep a misbehaving strategy contained.
How it's built
The architecture is built around a single pure decision engine that never touches the database, the network, or an exchange, so the exact same logic runs in a historical backtest, a live simulation, and real execution.
A trading decision is written as an order intent, then submitted and reconciled against the real fill by a separate process, which gives benefits for resiliency and observability. We have implemented risk controls and are extending the platform with AI-assisted strategy discovery.
