Source
People Data Labs
DeeplineWorkflow runpilot · inspect · write
Destination
Salesforce
How to Use People Data Labs Enrich Company in Deepline
Run People Data Labs Enrich Company through Deepline, route the contact discovery output, and write the reviewed result into Salesforce. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.
People Data Labs Enrich Company to Salesforce workflow
People Data Labs Enrich Company to Salesforce is a supported Deepline workflow path. Use it when an agent needs to run People Data Labs Enrich Company, inspect the returned fields, and write the reviewed result into Salesforce with run history, retries, and explicit failure states.
Use when
You need People Data Labs enrich company reviewed before it writes into Salesforce.
Source output
People Data Labs enrich company returns structured fields that Deepline records with provider attribution and row-level status.
Destination write
Salesforce receives only reviewed rows after the pilot command succeeds.
This workflow moves data from People Data Labs into Salesforce 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
- People Data Labs
- Destination app
- Salesforce
- Run time
- 3 min
- Difficulty
- beginner
- Agent surface
- Deepline CLI, API, and workflow scheduler
- Write policy
- Two-row pilot before destination writes
- People Data Labs auth
- Handled by Deepline -- connect once in the dashboard
- Salesforce auth
- Handled by Deepline -- connect once in the dashboard
- People Data Labs tier
- Any plan with the required API access
- Salesforce tier
- Salesforce API access required
Quickstart setup
curl -fsSL "https://deepline.com/api/v2/sdk/install" | bashFields agents can extract and verify
People Data Labs source data points
- Person profile
- full_name, job_title, linkedin_url, location
- Employment
- company_name, company_domain, role, seniority
- Company profile
- industry, size, locality, website
- Provider match metadata
- matched_on, confidence, source
Salesforce destination mapping
People Data Labs Person → Deepline normalized run output
email, linkedin_url, full_name, job_title, location, company_name
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 output → Salesforce CRM contact
email, name, title, company, run ID, external ID, mapped enrichment fields
Use an external ID or domain/email key so reruns update existing records instead of creating duplicates.
Salesforce report, queue, or task 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.
- People Data Labs account (Any plan with the required API access)
- Salesforce account (Salesforce API access required)
- 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.
curl -fsSL "https://deepline.com/api/v2/sdk/install" | bash - 02
Connect People Data Labs
Connect People Data Labs 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/peopledatalabs.
- 03
Connect Salesforce
Connect Salesforce as the destination. Use the provider page to confirm required scopes before writing data. Destination reference: https://deepline.com/integrations/salesforce.
- 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 person profile, employment, company profile plus provider attribution before writing anywhere.
deepline enrich --input leads.csv --output leads.enriched.csv --with 'result=peopledatalabs_enrich_company:{"domain":"example.com"}' --json - 05
Deploy the reviewed prompt
After the pilot is correct, deploy the exact prompt as a Deepline workflow. The mapping from People Data Labs to Salesforce is preserved with run history, retries, billing visibility, and a rollback tag.
> Use People Data Labs Enrich Company to enrich the input person, dedupe by domain and email, write results into Salesforce, 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 People Data Labs action, runs a pilot, records the output, and writes only reviewed rows to Salesforce.
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
People Data Labs 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 People Data Labs integration in Deepline, run the test endpoint, and then retry the workflow on --rows 0:2 with a broader filter.
Salesforce rejects the write
Cause: The destination field names, object IDs, campaign IDs, or permissions do not match the connected workspace.
Fix: Use the Salesforce 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 People Data Labs Enrich Company directly?
Yes. Deepline exposes the People Data Labs 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 Salesforce?
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
Clay (via webhook) → Salesforce
Use Deepline as a receiver for your Clay HTTP API column, then tell Claude to upsert each row into Salesforce Leads using the Clay row_id as External ID. Deepline handles OAuth refresh and rate-limit retries.
Apollo → Salesforce
Connect Apollo and Salesforce in Deepline, define your filter in the chat, and Claude runs the search + enrich + upsert. Deepline uses Apollo's person_id as External ID so reruns update existing Leads, never duplicate.
People Data Labs → Salesforce
Connect PDL and Salesforce in Deepline, describe the ICP as an ES-DSL query, and Claude runs search + enrich + Salesforce upsert using pdl_id as External_Id__c. Idempotent across reruns.
ZoomInfo → Salesforce
Connect ZoomInfo and Salesforce in Deepline, describe the persona + firmographics, and Claude runs the full search + enrich + upsert. ZoomInfo's personId lives as External_Id__c for clean dedup.
Smartlead (webhooks) → Salesforce
Point Smartlead webhooks at Deepline, describe the routing rules, and Claude updates the matching Salesforce Lead + creates an Activity on every event.
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.