Users submit quantitative strategy requirements, including trading instruments, strategy types (such as high-frequency, trend, arbitrage, etc.), risk preferences, etc. Professional team communicates with users to clarify requirement details and provide preliminary solutions and quotes.

Based on user requirements, develop strategies using platforms such as Python, MT4, cTrader, etc. Combine AI stock selection models, machine learning algorithms and other technologies to build efficient and stable quantitative strategies.

Conduct historical data backtesting on developed strategies to evaluate their performance under different market environments. Based on backtesting results, optimize strategy parameters to ensure risk-return ratio meets expected targets.

Assist users in deploying strategies to live trading environments and provide technical support and maintenance services. Regularly monitor strategy performance and provide strategy adjustment recommendations based on market changes to ensure long-term stable operation.