How the bulk permutator works
The tool parses pasted rows, asks you to confirm the name and domain columns, then runs the same ranked pattern generator used by the single-contact email permutator.
Paste your prospect rows
Paste the contacts you need email guesses for. Include either full name and domain, or first name, last name, and domain.
The gray rows are a placeholder. Paste your own list over them, with columns in whatever order they came in.Each contact needs a first name, last name, and domain, and you can leave any extra columns in place.Step 2 is where you point the generator at the name and domain columns.Step 3 turns every row into ranked email candidates you can copy or export as a CSV.
0 detected rows
Map the name and domain columns
After you paste rows, confirm which columns hold the names and the domain before generating candidates.
Add rows to map their columns.
Once you paste a list, the detected name and domain columns appear here for you to confirm.
Review and export
Generate candidates from the confirmed mapping, then copy or download the result.
No generated rows yet
Confirm the mapping in Step 2 and generate candidates to fill this table.
Input formats that work well
The cleanest input is one row per person with name and domain columns. A company website also works when the domain is clear. If a row has an existing email column, the tool can use that domain while still generating alternate patterns for the contact.
Best
Full name plus domain: Maya Chen, example.com.
Good
First name, last name, and website in separate columns.
Usable
A prospecting export with clear name and domain fields.
Needs review
Rows with nicknames, suffixes, department names, or company names in the person field.
The generator can normalize punctuation and accents, but it cannot know whether a pasted name is the legal name, preferred name, or a scraped company label.
CSV output
The downloaded CSV keeps one summary row per person, with one column for each generated email candidate plus normalized name fields, domain, domain status, provider evidence, SPF, DMARC, candidate count, and warnings. Copying to clipboard uses the same format. Before sending a campaign, check the list with the cold email CSV checker.
Domain checks
After generating candidates, dreamif.ai checks public DNS records for up to 100 unique domains. It does not check whether a private mailbox exists, and it does not send test messages.
Treat the output as candidate addresses, not a verified list. Narrow the candidates with a known company pattern, a public profile, a colleague email, or a separate verification step before any outreach.
How to prune a bulk export
Bulk generation is useful because it gives you likely address patterns fast. The export still needs a send-list pass. Treat the CSV as a research file first, then move only the best rows into the campaign file.
Campaign column
Keep one best candidate per contact, plus the normalized name and domain fields.
Research column
Keep alternate candidates here so the sending file does not target several versions of the same person.
Suppress rows
Remove rows with missing domains, company labels in the name field, or role accounts that do not fit the campaign.
Final QA
Run the reduced file through the CSV checker before import so blank fields and duplicate rows stay out of the sender.