AI powered trading insights for smarter investment decisions
TradeWise AI is an AI-driven paper-trading platform that lets users explore stock trades and understand the reasoning behind each signal. It brings market data, quantitative analysis, and plain-language explanations together in a dashboard, allowing users to simulate decisions without placing real trades.
I built TradeWise for Devs on Wall Street's flagship hackathon, where our team earned 3rd place. My goal was to create an end-to-end tool that makes trading analysis easier to explore and explain. By connecting a quantitative signal engine to a user-facing dashboard and explanation layer, I wanted users to test trade ideas while seeing why the system produced a signal.
One of the main challenges was coordinating market data and analysis across a web app and a separate Python API while keeping explanations grounded in the quantitative signal. The project keeps the model-generated signal as the basis for each trade insight and uses recent news as supporting context, rather than letting an AI-generated explanation replace the underlying analysis.
Building TradeWise gave me experience connecting a web frontend with a Python machine-learning service and shaping a workflow from market data to model output to user-facing explanation. I learned to treat data handling, quantitative analysis, and clear communication as connected parts of a usable financial application.