One question we keep getting: “How do I pull data out of a Revit® file if I don’t have Revit?” Fair question. An Autodesk® license runs several thousand dollars a year, and not everyone on the team needs the full software just to look at element quantities or check parameter values in a spreadsheet.

We built the CAD2DATA Pipeline to solve exactly this. It reads .rvt files directly and spits out a structured .xlsx workbook with all elements, all parameters, geometry data, bounding boxes — everything the model contains. No Revit on the machine. No Autodesk account. No plugins. Works on Windows® and Linux, runs offline.

Below are four ways to run it, from “just give me the data” to full automation pipelines.

Why would you even want Revit data in Excel®?

Seems obvious, but it’s worth spelling out because the use cases go way beyond “I want to see a schedule.”

The real value is when you take model data out of Revit’s walled garden and start working with it using tools that are actually good at data processing. Excel, Python™, Power BI, databases — that’s where analysis happens. Revit is a modeling tool, not an analytics platform.

Here’s what we see teams doing with the extracted data:

• Quantity takeoffs — element counts, areas, volumes, lengths. Apply unit rates in Excel, build cost estimates. Way faster than Revit schedules, especially across multiple models.
• Data validation — check if parameters are filled, naming conventions match, classification codes are correct. You can write a simple pandas script that checks 50,000 elements in seconds. Try doing that inside Revit.
• ERP integration — SAP, Oracle, MS Project — they all eat Excel or CSV for breakfast. The converter gives you structured data ready to import.
• AI and ML workflows — once you have tabular data, you can run classification, cost prediction, anomaly detection. Feed it into an LLM for analysis. None of that works with a closed .rvt binary.

What exactly comes out?

Every element in the model gets a row. Every parameter gets a column. The output workbook contains:

You also get a .dae file (3D geometry in COLLADA format) and optionally .pdf exports of sheet views.

Method 1: n8n™ workflows (zero code)

Fastest way to get started. You don’t need to write any code — just run one command and drag-and-drop in the browser.

git config --global core.longpaths true
git clone https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN.git
cd cad2data-Revit-IFC-DWG-DGN
npx n8n

That’s it. Open http://localhost:5678, import one of the ready-made workflows from DDC_n8n_Workflows&Pipelines/, set your file path in the “Set Variables” node, hit Execute. Done.

We ship 9 workflows out of the box:

Requires Node.js® 18+. That’s the only prerequisite.

Method 2: Command line

If you’d rather skip the browser and just convert files from the terminal — the converters are standalone executables. One input, one output.

RvtExporter.exe "C:\Projects\Building.rvt"

That gives you the default export. Want more? Add flags:

RvtExporter.exe "C:\Projects\Building.rvt" standard bbox schedule sheets2pdf

This gets you standard parameter data + bounding boxes for every element + schedule exports + PDF sheets. The output lands next to the input file.

Important gotcha on Windows: the repository has deeply nested folder names. You’ll hit “Filename too long” errors unless you enable long paths first:

git config --global core.longpaths true

And always use full absolute paths when calling the converter. Relative paths will fail silently or produce empty output. Use %CD%\ prefix or spell out the full path.

Here’s the full CLI reference for all converters:

Method 3: Python scripts

This is where it gets interesting for automation. The converter is just an executable — call it from Python with subprocess, then process the output with pandas or whatever you like.

Single file:

import subprocess

result = subprocess.run([
    r"C:\DDC\RvtExporter.exe",
    r"C:\Projects\Model.rvt",
    "standard", "bbox"
], capture_output=True, text=True, timeout=300)

print("OK" if result.returncode == 0 else result.stderr)

Batch convert a whole folder and then analyze:

from pathlib import Path
import subprocess, pandas as pd

converter = Path(r"C:\DDC\RvtExporter.exe")

for f in Path(r"C:\Projects").glob("*.rvt"):
    print(f"Converting {f.name}...")
    subprocess.run([str(converter), str(f), "standard", "bbox"],
                   capture_output=True, timeout=600)

# Now work with the data
df = pd.read_excel("Model_rvt.xlsx", engine="openpyxl")
walls = df[df["Category"].str.contains("Wall", case=False, na=False)]
print(f"{len(walls)} walls, total area: {walls['Area_m2'].sum():.1f} m²")

You’ll need pip install pandas openpyxl for the analysis part. The converter itself has no Python dependencies.

Method 4: Docker®

For reproducible environments or Linux servers. The converters are available through our APT repository, so the Dockerfile is straightforward:

FROM ubuntu:22.04
RUN apt-get update && apt-get install -y curl && \
    echo "deb [trusted=yes] https://pkg.datadrivenconstruction.io stable main" \
    > /etc/apt/sources.list.d/ddc.list && \
    apt-get update && \
    apt-get install -y ddc-rvtconverter ddc-ifcconverter
WORKDIR /data
ENTRYPOINT ["ddc-rvtconverter"]

docker build -t ddc-converter .
docker run --rm -v /your/projects:/data ddc-converter /data/Building.rvt /data/output/

We also have a Docker Compose setup with n8n + Qdrant (vector database) for AI-powered workflows. Check the repository for the compose file.

Scaling up: batch processing and CI/CD

Once you’ve converted one file, the natural next step is converting hundreds. A few options we’ve seen work well:

n8n batch workflow — import n8n_3_*.json. It walks a directory, converts each file, validates the output, and generates an HTML summary report. Set it up once, point it at a folder, let it run.

GitHub® Actions — put the converter in a CI pipeline. On every commit to your project repo, automatically convert all CAD files and store the Excel output as build artifacts. We’ve had teams set this up for nightly model validation.

AI coding assistants — the repository includes instruction files in AI_AGENTS_INSTRUCTIONS/ (including CLAUDE.md). Open the repo in Claude™ Code, Cursor™, or similar — and just describe what you want in plain English. “Convert all .rvt files in this folder and show me a summary of wall types.” The AI reads the instructions and runs the right commands.

How does this compare to other tools?

Honest comparison. Every tool has trade-offs.

The main advantage of BIMLink is bi-directional sync — you can push data back into Revit. We don’t do that (yet). If you need write-back, BIMLink is worth looking at. For read-only extraction, especially at scale or without licenses, the CAD2DATA pipeline is the better fit.

FAQ

Can you convert Revit to Excel without a license?

Yes. That’s the whole point of this tool. It reads .rvt files natively, no Revit installation required. Free, open source, works offline.

What data gets extracted from an RVT file?

Everything — element IDs, categories, families, types, all instance and type parameters, geometry (area, volume, length), location (level, room, coordinates), bounding boxes, materials. Schedules export as separate sheets. Custom parameters are included automatically.

Does it work with Revit 2026?

Yes. Supports versions 2015 through 2026. The converter reads the native file format directly — no version downgrade needed.

Can I batch convert multiple files?

Yes, no limit. Use the n8n batch workflow, a Python script looping over a directory, or a simple shell loop. The converter processes one file per call, so batch just means calling it in a loop. Parallelization works too.

Is it free for commercial use?

Yes. No license fees, no usage caps, no registration.

What format is the output?

.xlsx — standard Excel format. Opens in Excel, Google Sheets, LibreOffice, anything that reads Open XML. You also get .dae (3D geometry) and optionally .pdf sheet exports.

Best choice for Revit® to Excel® conversion

If it saves you time, a star on GitHub goes a long way.

Working with other formats? See our guides for IFC to Excel, DWG to Excel, DGN to Excel, RVT to Excel, and Revit to IFC conversion.

Revit® and AutoCAD® are registered trademarks of Autodesk, Inc. DWG™ is a trademark of Autodesk, Inc. Excel®, Windows®, Power BI® and Copilot™ are trademarks or registered trademarks of Microsoft Corporation. Docker® is a registered trademark of Docker, Inc. GitHub® is a registered trademark of GitHub, Inc. Node.js® is a registered trademark of the OpenJS Foundation. Python™ is a trademark of the Python Software Foundation. n8n™ is a trademark of n8n GmbH. Claude™ is a trademark of Anthropic, PBC. Cursor™ is a trademark of Anysphere, Inc. All other trademarks are the property of their respective owners. This project is not affiliated with or endorsed by any of the above companies.