Source
QuickEnrich
DeeplineWorkflow runpilot · inspect · write
Destination
Lemlist
How to Use QuickEnrich Company Contacts Search in Deepline
Run QuickEnrich Company Contacts Search through Deepline, route the contact discovery 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.
QuickEnrich Company Contacts Search API to Lemlist workflow
QuickEnrich Company Contacts Search API to Lemlist is a supported Deepline workflow path. Use it when an agent needs to run QuickEnrich Company Contacts Search API, inspect the returned fields, and write the reviewed result into Lemlist with run history, retries, and explicit failure states.
Use when
You need QuickEnrich company contacts search api reviewed before it writes into Lemlist.
Source output
QuickEnrich company contacts search api 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.
This workflow moves data from QuickEnrich 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
- QuickEnrich
- Destination app
- Lemlist
- Run time
- 3 min
- Difficulty
- beginner
- Agent surface
- Deepline CLI, API, and workflow scheduler
- Write policy
- Two-row pilot before destination writes
- QuickEnrich auth
- Handled by Deepline -- connect once in the dashboard
- Lemlist auth
- Handled by Deepline -- connect once in the dashboard
- QuickEnrich 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 --jsonFields agents can extract and verify
QuickEnrich source data points
- Record identifier
- id, url, domain, email, or provider key
- Matched entity
- person, company, account, page, query, or signal
- Provider attribution
- provider, action, run_id, retrieved_at
- Review status
- accepted, rejected, needs_review
Lemlist destination mapping
QuickEnrich Normalized provider record → Deepline normalized run output
id, url, domain, email, or provider key
Claude Code sees the normalized provider record as structured JSON, then Deepline adds provider name, action slug, run ID, retrieved timestamp, and row-level status.
Deepline normalized run output → Lemlist 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 list → Scheduled 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.
- QuickEnrich account (Any plan with the required API access)
- Lemlist account (Any plan with API access)
- Deepline CLI installed locally
- ~3 minutes
Step-by-step
- 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 - 02
Connect QuickEnrich
Connect QuickEnrich 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/quickenrich.
- 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.
- 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 record identifier, matched entity, provider attribution plus provider attribution before writing anywhere.
deepline enrich --input leads.csv --output leads.enriched.csv \ --with 'result=quickenrich_company_contacts_search:{}' \ --rows 0:2 --json # Review the pilot output, then map the result into Lemlist. - 05
Deploy the reviewed prompt
After the pilot is correct, deploy the exact prompt as a Deepline workflow. The mapping from QuickEnrich to Lemlist is preserved with run history, retries, billing visibility, and a rollback tag.
> Use QuickEnrich Company Contacts Search to enrich the input normalized provider record, dedupe by domain and email, write results into Lemlist, and show me the exact rows that changed before deploying the workflow.
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.
Why run it through Deepline
The workflow stays inspectable
Deepline exposes the QuickEnrich 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.
Troubleshooting
QuickEnrich 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 QuickEnrich 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.
FAQ
Can Deepline run QuickEnrich Company Contacts Search directly?
Yes. Deepline exposes the QuickEnrich 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.
Keep exploring
LinkedIn (post commenters) → Lemlist
Connect the LinkedIn scraper and Lemlist in Deepline, paste a post URL into the chat, and Claude scrapes commenters, runs the email waterfall, generates first lines, and drops everyone into your Lemlist campaign.
Lemlist (webhooks) → HubSpot
Point Lemlist at Deepline's webhook, tell Claude how to handle each channel (email vs LinkedIn), and HubSpot Contacts update with channel-tagged activity automatically.
Apollo → Lemlist
Connect Apollo and Lemlist in Deepline, describe the filter, and Claude pulls + verifies + imports. Lemlist's multi-channel sequences (email + LinkedIn) pair naturally with Apollo's firmographic filters.
Lemlist (webhooks) → Salesforce
Point Lemlist at Deepline, tell Claude how each channel event maps to Salesforce, and Deepline handles the routing + OAuth refresh.
HubSpot → Lemlist
Connect HubSpot and Lemlist in Deepline, describe the segment, and Claude pushes with hubspot_contact_id tagged so replies route back to the right Contact.
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.