Environment & runtime
Configure LEAN, Python environments, Docker where appropriate, and repeatable setup for a local workstation or cloud server.
Build and deploy QuantConnect LEAN on a cloud server or local machine, with a workflow that fits your strategy and brokerage.
Discuss your setupA trading engine is one part of a working trading system. We bring together the runtime, data, brokerage connection, deployment workflow, and operating controls around it.
Configure LEAN, Python environments, Docker where appropriate, and repeatable setup for a local workstation or cloud server.
Organize strategy projects, backtest results, paper environments, and live configurations into a workflow you can understand and maintain.
Configure and assess supported brokerage and data connections. Market coverage depends on the broker, engine, subscriptions, and account permissions.
Design strategy state, event records, restart procedures, and reconciliation around the way the algorithm actually trades.
The final deliverables, acceptance criteria, and support terms are agreed for each engagement.
A repeatable path from strategy code to an environment you can operate.
Tell us your engine, brokerage, markets, and the workflow you want to improve.