Problem
Financial analysis usually requires manual spreadsheets, time, and technical knowledge.
Solution
Users upload transaction data and receive structured insights, forecasts, anomalies, charts, and reports through an AI-assisted Streamlit interface.
Syed's Role
Python AI product engineering, analytics UX, reporting workflow
Highlights
Smart CSV parsing
Adaptive transaction analytics
Context-aware AI advisor
7/30/90 day forecasting
Anomaly detection
Financial health score
Professional PDF reports
Tech Stack
PythonStreamlitPandasNumPyScikit-learnSciPySQLitePlotlyMatplotlibReportLabAI/NLP API
Live Streamlit apps may wake on open depending on host sleep state.