AI data entry
Records arrive as emails, forms, scans and attachments, and somebody types them into the place they are supposed to live. Then somebody else finds the duplicate. This is that job, done continuously, by something that flags what it cannot read instead of guessing.
Concretely
- Enters records from emails, forms, scans and attachments.
- Moves data between spreadsheets, your CRM and your accounting software.
- Cleans up duplicates and inconsistent records.
- Checks new entries against what is already on file before adding them.
- Runs the recurring imports and exports, and flags anything that does not match.
Typing it in twice is where the errors live
Data entry is rarely one system. It is a form that becomes a spreadsheet row that becomes a CRM record that becomes a line in the accounting software, keyed by hand at each step by whoever had the time. Every hop is a chance to transpose a figure, and the error is usually found weeks later by someone who has to work backwards to the source.
It enters and tidies, it does not decide
That is the rule this job is hired under, and it is the one that makes unattended data entry safe. A record it cannot read confidently, a duplicate that might be two real customers with similar names, or a figure that disagrees with the source: all three go to a person with both versions side by side. Nothing is deleted on its own say-so.
Duplicates are a judgment, not a match
Two records with the same company name are sometimes one customer and sometimes a parent and a subsidiary who will both be annoyed if you merge them. Automatic deduplication that is confident about this is how a clean database becomes a wrong one. Here the near-matches are surfaced with the evidence and the merge is a person’s call.
The jobs this comes from
Sanaf holds thirty five written job descriptions. These are the ones behind this page.