OpenConstructionEstimate: The missing link between CAD (BIM) and Cost
26 November 2025

⚡️ Free n8n Workflow  PROJECT (REVIT) TO BUDGET: AUTOMATED COST ESTIMATION POWERED BY DECADES OF INDUSTRY STANDARDS

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⚡️ Free n8n Workflow

 PROJECT (REVIT) TO BUDGET

AUTOMATED COST ESTIMATION POWERED BY
DECADES OF INDUSTRY STANDARDS

Hi [subscriber:firstname | default:reader],

we have published a free open-source n8n pipeline that turns CAD (Revit 2015-2026) files into full cost and time estimates - using AI (LLM) and a vector database with over 55,000 construction work items across 9 languages.

DDC CWICR (Construction Work Items, Components & Resources) is an open database for construction cost estimation, covering the full spectrum of construction activities—from earthworks and concrete placement to specialized installation work.

Traditional roles - BIM manager, estimator, PM - are gradually ceasing to be “manual data operators.” The key competency is no longer how to manually check a table and find the right group, but how to correctly compile a prompt, adjust workflow parameters.

How it works:
1️⃣ Your BIM model converts to structured data
2️⃣ AI classifies elements and decomposes them into construction works
3️⃣ Vector search finds the most relevant pricing from the DDC CWICR database
4️⃣ Cost and time estimates generate instantly
Processing speed: 3-10 seconds per element group

Real-life example:
Using ChatGPT, it took about 30 minutes to estimate the cost of a standard Revit project from Autodesk (rac_basic_sample.rvt) (HTML estimates report can be found in our telegram group ⬇️).

📁 Output Files

Reports are saved to the project folder:

project_YYYY-MM-DD.html ← Interactive report with cost and time estimates (opens in browser)
project_YYYY-MM-DD.xls ← Excel-compatible spreadsheet

🌍 Supported Languages & Price Levels

CodeLanguagePrice LevelCurrency
ARArabicDubaiAED
DEGermanBerlinEUR
ENEnglishTorontoCAD
ESSpanishBarcelonaEUR
FRFrenchParisEUR
HIHindiMumbaiINR
PTPortugueseSão PauloBRL
RURussianSt. PetersburgRUB
ZHChineseShanghaiCNY

⬆️ This example is fully functional and ready to use right now - no additional setup required beyond API keys. Run it, explore the outputs, and understand how each stage works. But this is just the beginning.

n8n provides 400+ native integrations with platforms like Google Sheets, Notion, Slack, Airtable, databases (PostgreSQL, MongoDB), cloud storage, and more. Every node in this workflow is modular - you can:

🔄 Swap LLM providers (OpenAI ↔ Claude ↔ Gemini ↔ Grok)
📊 Connect to your ERP or project management system
📁 Export results to any destination (cloud storage, email, dashboards)
🔧 Modify any stage to match your estimation methodology

The workflow is yours to adapt. No restrictions.
No licensing fees. Full control.

If you want to see more workflows, follow our official channels, star this repository, and feel free to share your ideas or your own n8n solutions with the community.

📥 Download Workflow from GitHub

⭐ Star the repo if this saves you time

License

Database (DDC CWICR) - CC BY 4.0. Free to use, share, and adapt commercially. Attribution: "DDC CWICR by DataDrivenConstruction"

Code (workflows, scripts) - MIT. Free to use, modify, and distribute without restrictions.

Professionals who ignore workflow automation and AI-agents today have roughly 5 years before the construction industry moves past them. The tools are free and open. The data is open. The only question is who learns to use them first.

♻️ Feel free to share this post with colleagues who are facing data quality and calculation issues. This workflow might save hours of manual work - and it's completely free

 

We are gradually expanding a library of ready-to-use n8n workflows for automated construction cost estimation:

  • Image-based cost calculation
    Upload drawings, details or site photos, and the workflow will automatically extract structured data and match it with work items and resources from the DDC database.

  • Text-to-estimate (project description → cost breakdown)
    Provide a short natural-language description of the project, and the workflow will generate a structured cost estimate with work items, quantities and resource groups.

  • Anything related to data-driven construction workflows
    From file conversion and validation to syncing estimates with other systems, notifications, dashboards and custom integrations – any repetitive task in your cost and project data pipeline can become an n8n workflow.

🔗 Try the OpenConstructionEstimate app (free access to the database):
https://openconstructionestimate.com/

🔗 Discussion of the topic of calculating cost and time in Telegram channel:
https://t.me/datadrivenconstruction

🔗 n8n workflow for automating CAD–BIM → data (open-source):
https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto

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    • ALL THE CHAPTERS IN THIS PART
    • A PRACTICAL GUIDE TO IMPLEMENTING A DATA-DRIVEN APPROACH (8)
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    • LLM AND THEIR ROLE IN DATA PROCESSING AND BUSINESS PROCESSES (5)
    • ORCHESTRATION OF ETL AND WORKFLOWS: PRACTICAL SOLUTIONS (5)
    • SURVIVAL STRATEGIES: BUILDING COMPETITIVE ADVANTAGE (5)
    • 4D-6D and Calculation of Carbon Dioxide Emissions (4)
    • CONSTRUCTION ERP AND PMIS SYSTEMS (4)
    • COST AND SCHEDULE FORECASTING USING MACHINE LEARNING (4)
    • DATA WAREHOUSE MANAGEMENT AND CHAOS PREVENTION (4)
    • EVOLUTION OF DATA USE IN THE CONSTRUCTION INDUSTRY (4)
    • IDE WITH LLM SUPPORT AND FUTURE PROGRAMMING CHANGES (4)
    • QUANTITY TAKE-OFF AND AUTOMATIC CREATION OF ESTIMATES AND SCHEDULES (4)
    • THE DIGITAL REVOLUTION AND THE EXPLOSION OF DATA (4)
    • Uncategorized (4)
    • CLOSED PROJECT FORMATS AND INTEROPERABILITY ISSUES (3)
    • MANAGEMENT SYSTEMS IN CONSTRUCTION (3)
    • AUTOMATIC ETL CONVEYOR (PIPELINE) (2)

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    057 Speed of decision making depends on data quality

    Today’s design data architecture is undergoing fundamental changes. The industry is moving away from bulky, isolated models and closed formats towards more flexible, machine-readable structures focused on analytics, integration and process automation. However, the transition...

    060 A common language of construction the role of classifiers in digital transformation

    In the context of digitalization and automation of inspection and processing processes, a special role is played by classification systems elements – a kind of “digital dictionaries” that ensure uniformity in the description and parameterization...

    061 Masterformat, OmniClass, Uniclass and CoClass the evolution of classification systems

    Historically, construction element and work classifiers have evolved in three generations, each reflecting the level of available technology and the current needs of the industry in a particular time period (Fig. 4.2-8): First generation (early...

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    🚀 Welcome to the future of data in construction!

    You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

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    Stay ahead with the latest updates on converters, tools, AI, LLM
    and data analytics in construction — Subscribe now!

    🚀 Welcome to the future of data in construction!

    You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

    By downloading, you agree to the DataDrivenConstruction terms of use 

    Stay ahead with the latest updates on converters, tools, AI, LLM
    and data analytics in construction — Subscribe now!

    🚀 Welcome to the future of data in construction!

    You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

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    🚀 Welcome to the future of data in construction!

    You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

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    Theoretical Chapters:

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    What You'll Find on
    DDC Solutions:

    • CAD/BIM to spreadsheet/database converters (Revit, AutoCAD, IFC, Microstation)
    • Ready-to-deploy n8n workflows for construction processes
    • ETL pipelines for data synchronization between systems
    • Customizable Python scripts for repetitive tasks
    • Intelligent data validation and error detection
    • Real-time dashboard connectors
    • Automated reporting systems

    Connect Everything

    Theoretical Chapters:

    Practical Chapters:

    What You'll Find on
    DDC Solutions:

    • CAD/BIM to spreadsheet/database converters (Revit, AutoCAD, IFC, Microstation)
    • Ready-to-deploy n8n workflows for construction processes
    • ETL pipelines for data synchronization between systems
    • Customizable Python scripts for repetitive tasks
    • Intelligent data validation and error detection
    • Real-time dashboard connectors
    • Automated reporting systems

    Add AI & LLM Brain

    Theoretical Chapters:

    Practical Chapters:

    What You'll Find on
    DDC Solutions:

    • CAD/BIM to spreadsheet/database converters (Revit, AutoCAD, IFC, Microstation)
    • Ready-to-deploy n8n workflows for construction processes
    • ETL pipelines for data synchronization between systems
    • Customizable Python scripts for repetitive tasks
    • Intelligent data validation and error detection
    • Real-time dashboard connectors
    • Automated reporting systems
    ⚡️ Free n8n Workflow  PROJECT (REVIT) TO BUDGET: AUTOMATED COST ESTIMATION POWERED BY DECADES OF INDUSTRY STANDARDS
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