DievioEmail Pattern Detector
Identify observed company email patterns from known names and addresses. Compare matching formats by domain and see ambiguous or unmatched examples.
How to use this tool
- Paste CSV examples with first_name, last_name and email.
- Compare patterns grouped by company domain.
- Review exceptions and ambiguous matches before applying a pattern.
A worked example
Input
Jane Doe → jane.doe@example.com Alex Lee → alex.lee@example.com
Output
example.com: first.last — 2 observed examples
The names and known addresses support first.last for these two records. They do not establish a universal company rule.
What the result means
A pattern supported by several examples is a useful clue. Different teams, subsidiaries and names can use exceptions; keep ambiguous matches visible.
A domain alone cannot reveal its email pattern. Multiple patterns can fit short names; observed examples do not prove a company-wide rule.
Frequently asked questions
Can I detect an email pattern from a domain alone?
No. You need at least one known address paired with the correct first and last names. A domain alone contains no evidence about the employer’s naming convention.
Why does one address match more than one pattern?
Short names and initials can make different conventions produce the same address. Review every listed match and add examples with different names to reduce ambiguity.
Is this free, and are my inputs uploaded?
Use this tool without an account, subscription or credits. Processing and file exports run in your browser; the tool does not upload your inputs or send emails. Clear inputs to remove the current data. Inputs are not saved when you reload the page.
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