The Problem
BIM models contain vast amounts of project data — element quantities, material properties, cost parameters, schedule information — but extracting and presenting this data in a useful form typically requires either expensive BI tools or laborious manual exports. Most of the intelligence locked inside a Revit model never reaches the people who could use it.
The Approach
This project builds a pipeline from Revit to Python to interactive web dashboard:
- Extraction: Revit API scripts (via pyRevit or direct API access) pull element data from the live model
- Processing: Pandas cleans, aggregates, and structures the raw BIM data
- Visualization: Plotly and Streamlit render the data as interactive charts, tables, and filters accessible in any browser
The result is a dashboard that updates with the model — showing quantities by category, material take-offs, schedule progress, or custom parameter analysis depending on what the project requires.
Current State
This project is in active development alongside the Revit MCP server. Progress is documented in the GitHub repository. The work is part of a broader investigation into how Python can be used to make BIM data useful beyond the model environment.