AI Data Analysis Assistant

Self-service data analysis has always had a ceiling: the moment a business user hits a question that requires code, they’re stuck. This tool removes that ceiling. Upload a CSV, Excel, or JSON file, ask a question in plain English, and the system writes the Python, runs it, catches and fixes its own errors, and returns interactive charts with clear explanations.

How it works

  • Drop in a dataset and get an instant auto-report — stats, correlations, outliers, the works
  • Ask follow-up questions in natural language. The system writes Python under the hood, runs it in a sandboxed loop that catches and fixes its own errors, then returns Plotly visualizations + plain-language takeaways
  • Supports everything from basic EDA to predictive modeling and time-series forecasting

Architecture

Data Analysis Assistant architecture

The tech stack combines Python’s pandas for data aggregation, OpenAI’s GPT API for generating insights and writing code, Plotly for interactive visualizations, and an iterative error-handling system that ensures generated code works as intended. The prompts and orchestration can be customized for different organizations and use cases — from tailoring instructions to prioritize specific analyses to integrating domain-specific workflows.

Demo 1: Customer Churn Analysis

Churn rates by contract type and payment method, ML models to predict churn, and analysis of which features are most predictive of customer retention and loss.

Demo 2: Apple Financial Statement Analysis

Key financial metrics over time, comparison of latest financial ratios, and revenue/asset/free cash flow forecasting using Prophet.

Demo 3: Comparative Retailer Analysis

Side-by-side financial analysis of apparel retailers with bubble charts, box and violin plots, heatmaps, and waterfall charts.