AI-Powered Financial Intelligence Lab (Flagship Project)
This project currently lives in its own standalone public repository:
DataEden / fin-tech-intelligence-lab-public
The repository contains the public-facing documentation, notebooks, and project assets for the Financial Intelligence Lab — a live analytics and AI research system built around portfolio tracking, market data workflows, visualization, and AI-assisted commentary.
As this project evolves, it will be integrated into a broader portfolio publishing workflow, until then this standalone repository serves as the primary project source.
The documentation below is dynamically rendered from the project's GitHub repository README.
This site retrieves the public README from the repository and converts it into HTML for presentation on DataInsideData.com.
This keeps the repository as the single source of truth for project documentation, while the website acts as the presentation layer for easier browsing and portfolio storytelling.
Over time, this workflow may expand into a more automated CI/CD publishing pattern connecting private development work, public project documentation, and site rendering.
The documentation below is dynamically rendered from the project's GitHub repository. The site retrieves the repository README and converts it to HTML using the GitHub API and the Marked.js Markdown parser.
This ensures the repository remains the single source of truth while the website acts as the presentation layer.
This represents live Daily and weekly AI-generated reports produced within the project and surfaced here as part of the evolving analytics system built using Python, Pandas, and AI integration. It tracks real investment activity, performs daily and weekly analysis, and generates structured insights using OpenAI models.
- Manual portfolio snapshots (Robinhood)
- Yahoo Finance market data (
yfinance) - Dividend tracking logs
- Macro, market, and portfolio notes
These sources are merged into a unified analytical dataset used for time-series analysis, sector aggregation, and AI interpretation.
- Raw Data → Snapshots & Market Feeds
- Processing → Merged Analytical Dataset
- Analysis → EDA + Visualizations
- AI Layer → Structured Insight Generation
- Output → Markdown Reports & Blog Integration
The repository is the execution layer, while this page represents the documentation and presentation layer.
A core feature of this system is the integration of an AI insight engine that generates:
- Daily portfolio commentary
- Sector-level analysis
- Market interpretation
- Weekly summary reports
This transforms raw financial data into structured, readable intelligence, simulating workflows used in real-world analytics and research environments.
The system generates multiple analytical views of the portfolio, including:
- Portfolio value over time
- Capital vs market performance
- Market gain tracking
- Sector allocation trends
- Position weights
- Normalized asset performance
- Dividend income tracking
Visualization outputs will be displayed below as the dataset grows.