I am building an AI-driven agent dedicated to options trading that runs entirely through a browser-based interface. The core idea is simple: feed real-time market data into a learning model, surface high-quality option opportunities, and let the user approve or automatically execute those trades through a connected broker API. I already know I want everything accessible from the web, so the front-end should be lightweight yet responsive, while the back-end handles data ingestion, model inference, and order routing securely. A clean dashboard that shows live signals, historical performance, and adjustable strategy parameters is essential. Because this will revolve around options trading, the model needs to understand strike selection, expiry timing, Greek sensitivities, and implied volatility shifts. Historical data and continuous retraining must be part of the workflow so the agent can adapt as market conditions change. Deliverables • Fully functional web application (front-end + back-end) deployed on a cloud host of your choice • Machine-learning pipeline with documented training scripts, back-testing framework, and unit tests • Broker API integration capable of DATA FEED * SEND ALERT TO TELIGRAM AND SMS, WHATSAPP • Clear user documentation and setup instructions If you have experience combining machine learning with real-time trading on web platforms, I’d like to see a concise proposal outlining your approach, preferred tech stack, and estimated timeline.