Run People Data Labs Company Clean from Claude Code, route the contact discovery output through Deepline, and write the reviewed result into Attio. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider-doc links.
People Data Labs to Attio is a supported Deepline workflow path for Claude Code. Use it when an agent needs to run People Data Labs, inspect the returned fields, and write the reviewed result into Attio with run history, retries, and explicit failure states.
Best query match
“How do I connect People Data Labs to Attio with Claude Code?”
Source primitive
People Data Labs returns structured fields that Deepline records with provider attribution and row-level status.
Destination primitive
Attio receives only reviewed rows after the pilot command succeeds.
This workflow moves data from People Data Labs into Attio with Claude Code as the orchestration layer. It is strongest when you need a repeatable, inspectable handoff with explicit auth, cost math, and recovery steps.
First callable command
curl -s "https://code.deepline.com/api/v2/cli/install" | bash
deepline auth registerPeople 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 → Attio CRM contact
email, name, title, company, run ID, record ID, attributes
Keep the raw provider payload linked from the note when the destination schema has fewer fields than the source.
Attio list or workspace note → 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.
Install the Deepline CLI and register your workspace. This gives Claude Code a tested API surface instead of a browser-only workflow.
curl -s "https://code.deepline.com/api/v2/cli/install" | bash
deepline auth registerConnect People Data Labs in the Deepline dashboard. Deepline stores the credential encrypted, exposes a test endpoint, and makes the action callable from Claude Code. Provider reference: https://deepline.com/docs/providers/peopledatalabs.
Connect Attio as the destination. Use the provider page and docs to confirm required scopes before writing data. Destination reference: https://deepline.com/docs/providers/attio.
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_company_clean:{"name":"Example Corp"}' --jsonAfter the pilot is correct, ask Claude Code to deploy the exact prompt as a Deepline workflow. The mapping from People Data Labs to Attio is preserved with run history, retries, billing visibility, and a rollback tag.
> Use People Data Labs Company Clean to enrich the input person, dedupe by domain and email, write results into Attio, and show me the exact rows that changed before deploying the workflow.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.
Claude Code can read the People Data Labs action, run a pilot, inspect the output, and then write only reviewed rows to Attio.
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.
Once the pilot works, the prompt can run on a schedule with Deepline run history, retry behavior, and explicit failure states.
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.
Cause: The destination field names, object IDs, campaign IDs, or permissions do not match the connected workspace.
Fix: Use the Attio provider page to inspect the object schema, then map columns explicitly before running the full batch.
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.
Yes. Deepline exposes the People Data Labs action as an agent-callable API/CLI step, so Claude Code can run a pilot, inspect the JSON, and then deploy the same logic as a workflow.
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.
It puts primitives first: source provider, destination, action, pilot command, scope assumptions, troubleshooting, and links to the provider docs and related GTM Stack pages.
Connect Apollo and Attio in Deepline, tell Claude your ICP filter + the Attio list to assign, and the workflow runs. Deepline uses Attio's matching_attribute=email_addresses so reruns update existing People, never duplicate.
Connect PDL and Attio in Deepline, describe the ICP in plain English (or ES-DSL for power users), and Claude runs search + enrich + Attio upsert. matching_attribute=email_addresses keeps reruns idempotent.
Connect ZoomInfo and Attio in Deepline, describe the persona, and Claude runs ZoomInfo search + enrich + Attio upsert. matching_attribute=email_addresses keeps it idempotent.
Connect Attio and Instantly in Deepline, pick the Attio list or filter, and Claude runs the export + Instantly import with attio_record_id for reply attribution.
Connect Attio and Smartlead in Deepline, pick the list or filter, and Claude runs the export + Smartlead import.
Run it on Deepline or fork the full skill pack on GitHub. Either way, the code is yours to read and change.