WorkerKitJoin the waitlistAI workers for Data Entry
AI workers for data entry transcribe information from emails and forms into your systems accurately. WorkerKit's firewall sets which records they may create and update.
- School Email to Calendar Language model Scan school emails and create complete calendar events organized by child name.
- Project Brain Daily Update Language model Every evening, pulls recent Krisp meetings and files the ones about your project into the project brain, once each.
- Spec to Linear Issues Language model Turns a spec you paste into the run message into Linear issues, one per deliverable, written to your team's standard and never duplicated.
- Project Brain Session Log Language model Logs a useful agent session into the project brain's daily notes.
- Project Brain Interview Ingest Language model Files a customer call into the project brain: interview note, account update and insight evidence, once per call.
- Project Brain Meeting Ingest Language model Files a meeting transcript into the project brain with proper frontmatter and a conventional commit.
What is a Data Entry AI worker?
A data-entry AI worker is an AI agent set up to run the data entry job unattended, taking information from an email, form, or document and transcribing it into the right fields of a system of record. It typically touches Gmail and Outlook mail, Google Drive and SharePoint files, and HubSpot, Salesforce, Notion, or task boards, writing only into the records and fields you have approved.
What these workers do
Log inbound leads into HubSpot
Reads a new lead email and creates a HubSpot contact with name, company, and message in the right fields, so nothing is retyped by hand.
Enter form responses into Notion
Takes submitted form details and writes them as a structured row in a Notion database, keeping intake consistent and searchable.
Create tasks from request emails
Reads a request in Outlook and creates a task in Asana or ClickUp with title, owner, and due date filled from the message.
Record expenses into a sheet
Takes receipt details and writes vendor, date, and amount into a Google Sheets tracker so the expense log stays current.
How a Data Entry AI worker runs
What it connects to
When it runs
What stays under your control
Data Entry questions, answered.
Can a data-entry AI worker create records in my CRM?
Yes, if you grant create permission, and only in the pipeline or fields you scope. A data-entry worker writes new HubSpot or Salesforce records from the emails and forms you point it at. WorkerKit limits exactly which fields it may fill, so it populates what you intend and nothing outside that grant.
How is a data-entry worker different from extraction?
Data entry transcribes information into a system of record, extraction pulls fields out of a document into structured data. A data-entry worker's output lands as a live CRM record or task. An extraction worker's output is the structured values themselves. Often extraction feeds data entry, but the write into your system is the data-entry job.
Will a data-entry worker put information in the wrong field?
It writes only into the fields you map, and WorkerKit blocks everything else. You define which source detail goes to which field, and a data-entry worker follows that mapping on every item. The firewall stops it writing to fields outside the grant, and each write is logged so you can verify accuracy.
Can a data-entry worker handle sensitive information?
Yes, and you can redact sensitive source details so they are never transcribed. If an intake email holds data a record should not store, WorkerKit redacts it before the data-entry worker reads it. Only the fields you approved get written, keeping sensitive material out of your system of record.