Auto-anonymisation: what gets removed
RemakeCV removes names, contact details, employer names, institutions and other identifying markers from a CV while preserving achievements, metrics and seniority.
RemakeCV's auto-anonymisation strips identifying information while keeping the substance intact. The candidate's name is replaced with a professional headline such as "Lead Data Scientist with 8 years of experience in e-commerce". Employers become industry descriptors, contact details are redacted, and quantified achievements are deliberately preserved.
What gets removed or replaced?
| Element | What happens |
|---|---|
| Candidate name | Replaced with a professional headline — e.g. "Senior Software Engineer with 10+ years of experience in FinTech" |
| Email, phone, address | Replaced with [REDACTED] |
| LinkedIn, YouTube, website and social URLs | Replaced with [REDACTED] |
| Employer names | Replaced with an industry-and-type descriptor |
| Educational institutions | Replaced with a short neutral descriptor |
| Locations | Generalised to city or region level |
| Proprietary internal tool names | Genericised |
| Contact details inside bullet points | Removed |
| Photographs | Never present — the output is rebuilt from extracted text |
What replaces the candidate's name?
Not initials, and not a blank. The name is replaced with a professional headline summarising seniority, years of experience and specialisation:
| Original | Anonymised |
|---|---|
| Jane Doe | Lead Data Scientist with 8 years of experience in e-commerce |
| — | Senior Software Engineer with 10+ years of experience in FinTech |
This is deliberate. A blank where a name should be tells a hiring manager nothing; a headline tells them immediately whether the candidate is worth reading, without revealing who they are.
What is deliberately kept?
This is the part that distinguishes a useful anonymised CV from a useless one.
- Quantified achievements. "Managed a team of 10 and a budget of $500,000" survives verbatim. Strip the numbers and you have removed the evidence the client is hiring on.
- Job titles and seniority. The client still needs to know whether this is a manager or a director.
- Date ranges and durations. Career progression is visible.
- Skills, tools and technologies. Industry-standard tools are kept verbatim — Jira, Salesforce, AWS. Only proprietary internal tool names are genericised, since "AcmeCorp Internal Dashboard" identifies the employer.
- Industry context. An employer becomes a short descriptor of industry and type — for example
Global fintech company; public. Placeholders like "Company A" are explicitly forbidden. - Acronyms. KYC, AML, ERP and the like are preserved rather than expanded, because expanding them changes the meaning a specialist reads.
The design goal is stated plainly: maximum insight, zero bias. Anonymisation that also removes the substance defeats the purpose — the client cannot assess the candidate and asks for the identified version anyway.
How are employer names replaced?
With a short descriptor giving industry and type, capped at 12 words. Stripe becomes Global fintech company; public. Size is only added where it is definitively known rather than inferred — if uncertain, it is omitted entirely.
This keeps the CV assessable. "Five years at a tier-one investment bank" tells a hiring manager what they need; "five years at [REDACTED]" tells them nothing.
Why must I still review the result?
Because identifying information hides in places pattern-matching does not reach:
- Project or product names unique to one employer
- Internal job titles that only one company uses
- Company-specific acronyms in bullet points
- Distinctive career paths — a single named role at a small organisation can be identifying on its own
- Named awards tied to one company
- Acronyms, which are deliberately preserved and can be employer-specific
Automation catches the structured fields reliably. The long tail is a human judgement call, and the consequence of missing one is a candidate identified in what was supposed to be a blind process.
Before sending an anonymised CV, read it once as a stranger trying to identify the person. Automation reliably handles the structured fields; the long tail below is a human judgement call, and the cost of missing one is a candidate identified in a process that was supposed to be blind.
Before anonymising, it is worth confirming nothing was dropped in extraction — see checking what was extracted.
Can I anonymise a CV I processed earlier?
Yes. Open it from CV history and anonymise it there. No re-upload and no credit — useful when a client switches to a blind process mid-shortlist.
What if I only want to remove some details?
Edit the fields directly in the editor. Some clients want the employer visible but the name hidden; that is an edit rather than a full anonymisation.
For anything identifying that anonymisation left behind — a project codename, an internal job title — change the wording in the editor before downloading. Replacing beats deleting: "Led delivery of Project Nightingale" → "Led delivery of a group-wide CRM migration" keeps the achievement legible.
Frequently asked questions
- Does anonymisation remove the candidate's achievements?
- No. Quantified achievements are explicitly preserved. 'Managed a team of 10 and a budget of $500,000' stays intact — only identifying details are removed.
- What happens to employer names?
- They are replaced with a neutral descriptor of industry and type, for example 'a global management consultancy' or 'a mid-size SaaS business', so the client can still judge relevance.
- Should I check an anonymised CV before sending it?
- Yes, always. Identifying details can hide in places automation does not reach — a project name, a niche job title, a company-specific acronym. Review before sending.
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