QuantDesk: Safe AI Trading Infrastructure

QuantDesk is an AI-powered quantitative trading infrastructure platform designed to make autonomous trading systems more measurable, auditable, and safe. Many trading agents combine research, model reasoning, and broker execution inside one loosely controlled workflow. QuantDesk deliberately separates those responsibilities. Python is used for offline research, feature engineering, backtesting, experiment validation, and read-only AI/MCP tooling. A C#/.NET runtime is the sole execution authority, enforcing deterministic risk controls, account and asset checks, broker reconciliation, order lifecycle tracking, and fail-closed execution gates. The system evaluates equities and crypto opportunities, but a model cannot place a trade simply because it produced a signal. Before execution, QuantDesk checks whether the research artifact is validated and current, whether market and account state are healthy, whether exposure is attributable, and whether spread, slippage, fees, and risk constraints are acceptable. Every approved paper trade is reconciled against actual broker fills and recorded as evidence for later analysis. The project currently integrates Alpaca paper trading, a dedicated research MCP server, an external market-data MCP boundary, containerized services, automated tests, durable experiment records, and a bounded BTC/USD diagnostic lifecycle that has already exercised the broker entry, exit, recovery, and final zero-exposure reconciliation path. For the AI Infra Summit, QuantDesk demonstrates an infrastructure-first approach to financial AI: models can propose decisions, but deterministic systems govern whether those decisions are allowed to reach the market. The goal is not simply to automate trading; it is to build the control plane required for trustworthy autonomous financial agents.