18steps·7providers·SQLyou own

Work Email CSV from LinkedIn Profiles

Resolve verified work emails for a CSV of LinkedIn profile URLs.

Shared June 2026

  1. 1

    Install & authenticate

    $ curl -fsSL "https://deepline.com/api/v2/sdk/install" | bash

  2. 2

    Test out this play on my data

What this workflow does

Resolve verified work emails for a CSV of LinkedIn profile URLs.

Work Email CSV from LinkedIn Profiles (Deepline play "person-linkedin-to-email-batch", version 1). Resolve verified work emails for a CSV of LinkedIn profile URLs. Pipeline: 18 steps, 7 providers, processes input rows as a dataset. Inputs: csv, columns. Outputs: email, email_source, email_validated, email_found_and_valid, miss_reason.

Inputs you need

Bring these fields

  • csv

Outputs you get

Produced by the run

  • email_result
  • email
  • email_source
  • email_validated
  • email_found_and_valid
  • miss_reason
  • email_result.prospeo_verified_email
  • email_result.native_contact
  • email_result.findymail_business_profile_email
  • email_result.lusha_linkedin_email
  • email_result.contactout_work_email
  • email_result.forager_work_email
  • email_result.leadmagic_social_email

How it works

  1. Step 1

    Read input rows

    play entry

  2. Step 2

    Dataset rows

    over linkedin_url

Cost/latency when available

This public page does not show cost or latency yet. Deepline only displays those metrics when the published package has safe, comparable run samples, and cost is always shown in Deepline credits.

Common edits

  • Rename the copied play before the first run so it is owned by your workspace.
  • Map your CSV headers into the expected input fields and add status or miss_reason columns.
  • Keep stable step, fetch, dataset, and play-call ids so retries and durable receipts stay useful.
  • Edit the final projection before scale so the output table matches your CRM or campaign import.

Use it when

  • You need data from Prospeo, Leadmagic, Deepline, Findymail, Lusha, Contactout and Forager in one pass.
  • You want a repeatable pipeline instead of one-off lookups.
  • You want an agent or teammate to run the same workflow on demand.

Related workflows

Personal Email CSV Finder

csv, columns → personal_email, email_source, email_validated

Work Email from LinkedIn Profile

linkedin_url → email, email_source, email_validated

Personal Email Finder

first_name, last_name, linkedin_url → personal_email, email_source, email_validated

Run or fork with Deepline CLI

Work Email CSV from LinkedIn Profiles is a Deepline play. Inputs: csv. Outputs: email_result, email, email_source, email_validated, email_found_and_valid, miss_reason, email_result.prospeo_verified_email, email_result.native_contact, email_result.findymail_business_profile_email, email_result.lusha_linkedin_email, email_result.contactout_work_email, email_result.forager_work_email, email_result.leadmagic_social_email.

# Inspect the contract

$ deepline plays describe prebuilt/person-linkedin-to-email-batch --json

# Copy to an owned scratchpad

$ deepline plays get prebuilt/person-linkedin-to-email-batch --source --out person-linkedin-to-email-batch-scratchpad.play.ts

# Check before running

$ deepline plays check person-linkedin-to-email-batch-scratchpad.play.ts

# Paste into Claude Code, Cursor, or Codex.

$ Use the deepline-gtm skill's plays recipe to turn the Deepline play "Work Email CSV from LinkedIn Profiles" (https://deepline.com/p/deepline/person-linkedin-to-email-batch) into an editable scratchpad play. Inputs: csv. Outputs: email_result, email, email_source, email_validated, email_found_and_valid, miss_reason, email_result.prospeo_verified_email, email_result.native_contact, email_result.findymail_business_profile_email, email_result.lusha_linkedin_email, email_result.contactout_work_email, email_result.forager_work_email, email_result.leadmagic_social_email. The .play.ts file is the source of truth: copy the play, rename it for this user's workflow, encode input mapping/validation/status/output projection in the play, and iterate there instead of doing one-off CSV post-processing. Keep stable dataset names, dataset row keys, and step/fetch/play-call ids across edits. Provider tool calls reuse paid work by play, tool, semantic input, auth scope, provider action version, and cache policy unless you intentionally change those inputs or refresh stale data. # install Deepline if the CLI is missing curl -fsSL "https://deepline.com/api/v2/sdk/install" | bash # inspect the live contract deepline plays describe prebuilt/person-linkedin-to-email-batch --json # copy to an owned scratchpad, then rename the play inside the file before first run deepline plays get prebuilt/person-linkedin-to-email-batch --source --out person-linkedin-to-email-batch-scratchpad.play.ts # edit person-linkedin-to-email-batch-scratchpad.play.ts: set an owned play name, add mappings/validation/status/miss_reason/final columns deepline plays check person-linkedin-to-email-batch-scratchpad.play.ts # run the scratchpad on your data deepline plays run --file person-linkedin-to-email-batch-scratchpad.play.ts --input '{"csv":"<your-file.csv>"}' --watch # only for an exact one-off with no edits or custom output deepline plays run prebuilt/person-linkedin-to-email-batch --input '{"csv":"<your-file.csv>"}' --watch Play spec (JSON): https://deepline.com/api/v2/shared-plays/prebuilt-person-linkedin-to-email-batch

Version

v1 · Shared June 2026 · Unlisted page