Anonymize a CSV for Gemini — in your browser
CSV exports from a CRM, help desk, or billing system are full of names, emails, phone numbers, and account IDs. Data Alias parses the file in your browser — delimiter inference, quoted fields, commas and line breaks inside cells all handled — and builds a safe copy that keeps the rows, columns, and repeated-value relationships your analysis needs.
How it works, step by step
Upload your CSV
Drop the file into the workspace. It is parsed locally in your browser tab — up to 10 MB on Free, and up to 100 MB / 200,000 rows with streaming on Pro. Nothing is uploaded to a server at any point.
Review the suggested column rules
Headers like name, email, phone, and customer_id get suggested types with matching rules — alias for people and companies, mask for phone numbers, remove for credentials. Every cell is also scanned for emails, phones, IP addresses, and API keys hiding in free-text columns. Suggestions are never auto-confirmed: you adjust and approve them.
Download the safe copy for Gemini
Export a .safe.csv with the original column order, every row, and UTF-8 BOM intact — aliases like PERSON_001 instead of identities. Upload that copy to Gemini, and keep the mapping on your machine to translate the answer back.
Example: customers.csv → customers.safe.csv
Why anonymize before Gemini?
Human reviewers can read consumer conversations
Google documents that conversations in the consumer Gemini apps may be read by human reviewers to improve the service. That is a documented process, not a leak — and it is exactly why pasting a customer list into a consumer chat deserves an anonymized copy instead of the original.
Source: Google Gemini Apps privacy notice ↗A reviewed conversation should contain aliases, not identities
If a conversation can be sampled for review, the safest version of your file is one where the reviewer would see PERSON_001 and EMAIL_002 rather than real people. The analysis quality is the same; the exposure is not.
Source: Google Gemini Apps privacy notice ↗These are Google's own documented behaviors as of our research (July 2026). Policies and defaults change — an anonymized copy is the control that doesn't depend on them.
What to know about csv files
Aliases stay consistent across rows
The same source value always maps to the same alias within a session — John Smith is PERSON_001 in row 8 and in row 8,000. Joins, group-bys, and repeat-customer patterns survive anonymization, which is exactly what one-shot find-and-replace breaks.
Structure is preserved on export
The safe copy keeps original column order, all rows, empty cells, and proper CSV quoting, and adds a UTF-8 BOM so it opens cleanly in Excel. Numeric columns are preserved by default so totals and aggregates still compute.
Common questions
- Will the same person get the same alias in every row?
- Yes. Within a session the same source value always maps to the same alias (PERSON_001, COMPANY_002, and so on), so joins and repeated identifiers remain analyzable. With the Pro alias vault you can keep that mapping consistent across files, too.
- Does the safe copy keep my columns and rows intact?
- Yes. The export preserves original column order, every row, and empty values, quotes fields correctly, and includes a UTF-8 BOM. The file downloads as name.safe.csv next to your original — the original is never modified.
- What about sensitive values hiding in free-text columns?
- Every cell is scanned for emails, phone numbers, IPs, and credential patterns regardless of the column name. Text columns with detections get an in-place "alias detected values" suggestion, and the pre-download check warns about detected values you chose to keep.
An honest note on detection
Data Alias reduces exposure risk but cannot catch every sensitive value, and no automated detector can. That is why nothing is applied without your review: check the safe copy before you share it with Gemini or anyone else.
No account needed. Files stay in your browser — verify it yourself.