AI Cost Estimation from Revit/IFC Models with GPT-4 & Claude

This n8n workflow estimates construction costs for grouped BIM/CAD elements by analyzing Revit/IFC models or existing XLSX files. It optionally triggers a local RvtExporter.exe to extract grouped data (volumes/areas already aggregated), builds structured prompts with rules, and queries selected LLMs like GPT-4 or Claude to identify materials, select pricing units, and compute per-unit prices and totals with confidence scores.

The workflow parses LLM outputs to enrich data with KPIs like cost percentages and rankings, aggregates project totals by material/category, and exports a comprehensive multi-sheet XLSX report plus a polished HTML executive summary featuring charts and top groups. Benefits include rapid, AI-accurate cost insights without manual spreadsheets, reducing estimation time from hours to minutes.

Ideal for architects, contractors, and estimators handling Revit/IFC projects. Use cases: Pre-bid cost analysis, value engineering, material optimization in Germany/EU standards, or integrating into larger AEC workflows. Requires LLM credentials; Windows optional for extraction.