// Deepline workflow
Lusha logo

Source

Lusha

DeeplineWorkflow runpilot · inspect · write
Lemlist logo

Destination

Lemlist

intermediate3 minLast updated May 30, 2026

How to Use Lusha Enrich Person in Deepline

Run Lusha Enrich Person through Deepline, route the signal-based selling output, and write the reviewed result into Lemlist. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.

00Best starting point

Lusha Enrich Person to Lemlist workflow

Lusha Enrich Person to Lemlist is a supported Deepline workflow path. Use it when an agent needs to run Lusha Enrich Person, inspect the returned fields, and write the reviewed result into Lemlist with run history, retries, and explicit failure states.

Use when

You need Lusha enrich person reviewed before it writes into Lemlist.

Source output

Lusha enrich person returns structured fields that Deepline records with provider attribution and row-level status.

Destination write

Lemlist receives only reviewed rows after the pilot command succeeds.

01Primitives first

This workflow moves data from Lusha into Lemlist with Deepline as the orchestration layer. It fits cases that need a repeatable, inspectable handoff with explicit auth, cost math, and recovery steps.

Source app
Lusha
Destination app
Lemlist
Run time
3 min
Difficulty
intermediate
Agent surface
Deepline CLI, API, and workflow scheduler
Write policy
Two-row pilot before destination writes
Lusha auth
Handled by Deepline -- connect once in the dashboard
Lemlist auth
Handled by Deepline -- connect once in the dashboard
Lusha tier
Any plan with the required API access
Lemlist tier
Any plan with API access

Quickstart setup

npm install -g deepline@latest && npm exec --yes --package=deepline@latest -- deepline setup --json
02Data map

Fields agents can extract and verify

Lusha source data points

Lead identity
name, title, seniority, linkedin_url
Contact details
email, phone, mobile_phone, confidence
Company profile
company_name, domain, industry, headcount
Compliance context
source, retrieved_at, suppression_status

Lemlist destination mapping

Lusha PersonDeepline normalized run output

email, linkedin_url, name, title, seniority

Claude Code sees the person as structured JSON, then Deepline adds provider name, action slug, run ID, retrieved timestamp, and row-level status.

Deepline normalized run outputLemlist Campaign lead

email, name, company, campaign_id, run ID, personalization variables

Map only reviewed personalization fields to avoid sending raw provider text directly.

Lemlist campaign lead listScheduled Deepline workflow

review status, dedupe key, rollback tag, next run window

After the two-row pilot is approved, the same mapping becomes a scheduled workflow with run history, retries, and loud failures.

03What you need
  • Lusha account (Any plan with the required API access)
  • Lemlist account (Any plan with API access)
  • Deepline CLI installed locally
  • ~3 minutes
04Walkthrough

Step-by-step

  1. 01

    Install Deepline

    Install the Deepline CLI and register your workspace. This gives agents a tested API surface instead of a browser-only workflow.

    npm install -g deepline@latest && npm exec --yes --package=deepline@latest -- deepline setup --json
  2. 02

    Connect Lusha

    Connect Lusha in the Deepline dashboard. Deepline stores the credential encrypted, exposes a test endpoint, and makes the action callable from the CLI or an agent. Provider reference: https://deepline.com/integrations/lusha.

  3. 03

    Connect Lemlist

    Connect Lemlist as the destination. Use the provider page to confirm required scopes before writing data. Destination reference: https://deepline.com/integrations/lemlist.

  4. 04

    Run a two-row pilot

    Run the smallest useful pilot first. The row range is end-exclusive, so --rows 0:2 tests exactly two rows before a larger batch. Inspect lead identity, contact details, company profile plus provider attribution before writing anywhere.

    deepline enrich --input leads.csv --output leads.enriched.csv --with 'result=lusha_enrich_person:{}' --json
  5. 05

    Deploy the reviewed prompt

    After the pilot is correct, deploy the exact prompt as a Deepline workflow. The mapping from Lusha to Lemlist is preserved with run history, retries, billing visibility, and a rollback tag.

    > Use Lusha Enrich Person to find new buying signals for our target accounts, score each signal by urgency and fit, write the best person into Lemlist, and post anything needing human review before activation.
05Cost math

What this costs to run

For 1,000 leads: Pilot first; Deepline credits depend on the selected action and successful results.

Deepline reports Deepline credits and run history. Provider subscriptions or API entitlements stay in the connected provider account.

06Why Deepline

Why run it through Deepline

The workflow stays inspectable

Deepline exposes the Lusha action, runs a pilot, records the output, and writes only reviewed rows to Lemlist.

Provider docs and GTM Stack pages are linked

The workflow links the Deepline provider docs, the GTM Provider Directory profile, and related workflow pages so agents can cite the right source before they call a tool.

The same prompt can become a schedule

Once the pilot works, the prompt can run on a schedule with Deepline run history, retry behavior, and explicit failure states.

08Recovery

Troubleshooting

Lusha returns no rows

Cause: The input filter is too narrow, credentials are missing a required scope, or the provider account tier does not expose the action.

Fix: Open the Lusha integration in Deepline, run the test endpoint, and then retry the workflow on --rows 0:2 with a broader filter.

Lemlist rejects the write

Cause: The destination field names, object IDs, campaign IDs, or permissions do not match the connected workspace.

Fix: Use the Lemlist provider page to inspect the object schema, then map columns explicitly before running the full batch.

The workflow works once but fails on a schedule

Cause: A required ID, campaign name, or date window was hardcoded in the prompt instead of resolved during each run.

Fix: Move IDs into workflow inputs or a lookup step, and keep the scheduled prompt focused on the durable business rule.

09Reference questions

FAQ

Can Deepline run Lusha Enrich Person directly?

Yes. Deepline exposes the Lusha action as an agent-callable API and CLI step, so you can run a pilot, inspect the JSON, and then deploy the same logic as a workflow.

Should I write directly to Lemlist?

Run a two-row pilot first, inspect provider attribution and dedupe fields, then allow the workflow to write to the destination. This keeps the assertion intact without using a test hack.

How does this page help agents trust the workflow?

It puts primitives first: source provider, destination, action, pilot command, scope assumptions, troubleshooting, and links to the provider docs and related GTM Stack pages.

11Run this

Want this workflow pre-configured?

Run it on Deepline or fork the full skill pack on GitHub. Either way, the code is yours to read and change.