PDF & Documents
Anonymize a Word resume by removing contacts and photos
Upload a DOCX CV and choose what to remove: email, phone, profile links, dates, photos. Names and addresses are removed when you type them in. You get a new DOCX.
or drop them here
- DOCX
- Up to 100 documents
1 prepared source file · 309 bytes
- Processed documents: 1
- Removed text matches: 1
- Removed media: 0
anonymized.docx · removal-manifest.csv · manifest.json
One clear job, from source to download
- 1
Add the source
Supported formats and limits are visible before the upload.
- 2
Confirm the settings
Review the exact source, options, units and access before processing.
- 3
Inspect and download
Check the preview and warnings, then unlock the complete package.
Anonymise a Word CV before it goes to reviewers
What you upload and what gets removed
You upload CVs as DOCX files, up to 100 documents in one job. You choose the categories to remove: email addresses, phone numbers, profile links, dates such as a birth date, and photos or other embedded media. Names and street addresses have no reliable pattern. They are only removed when you type in the exact values. If you leave them out, they stay in the file. Everything else stays as written.
The anonymised copy and the removal log
You get a new DOCX for each CV, with tables, headings and styles kept. Your original upload is not changed. removal-manifest.csv lists the count and category of every removal, so you can see what was taken out. manifest.json records a fingerprint of the source and output files, which lets a reviewer confirm they hold the same files you processed. Open one CV next to its log before you pass the batch on.
The settings and what stays your call
The main setting is the list of categories to remove: contact details, photo, age and birth date, and profile links. Pick only what your process calls for. Removing these signals does not make a CV free of bias. School names, career gaps, phrasing and language can still point to a person. Treat the output as a review copy. Decisions about fairness and compliance in your hiring process stay with you and your advisers.
Questions before you run it
Which details does it remove from a CV without me typing anything?
Pattern-based categories are handled on their own: email addresses, phone numbers, profile links, dates such as a birth date, and embedded media including the photo. Everything else stays as written.
Why are candidate names and addresses not removed automatically?
A personal name or street address has no reliable pattern, so the job fails closed rather than guessing. You supply the exact values you want taken out, otherwise those fields remain in the output.
Does the anonymised file stay a usable DOCX?
Yes. A new DOCX is written with the selected matches removed and the original upload is left untouched, so tables, headings and styles survive the pass.
How do I prove what was removed?
The package includes removal-manifest.csv with the count and category of every removal, and manifest.json carrying source and output hashes. That pair is what you hand to a reviewer or keep on file.
Is a blind CV produced this way actually free of bias?
No. Taking out contact details and the photo removes obvious signals, but school names, career gaps, phrasing and language can still identify a candidate. Treat the output as a review copy, not a compliance guarantee.