Deepline for GTM Engineers

Who this is for

GTM engineers are the fastest-growing non-technical user group for AI coding agents. If you live in Claude Code, Cursor, or Codex and need reliable, programmable enrichment without spreadsheet-based tools, Deepline is the missing layer.

• You write scripts, not formulas. Your workflow belongs in a git repo, not a SaaS UI.
• You need agents to run enrichment autonomously — not click through a browser.
• You have provider API keys (Apollo, Crustdata, PDL) and want to use them directly.
• You process thousands of rows and can't afford arbitrary table caps or auto-run credit burn.

5 workflows GTM engineers run with Deepline

deepline enrich --input badge-scans.csv --output enriched.csv \
  --with-waterfall "email" \
  --with 'apollo=apollo_people_match:{"first_name":"{{First Name}}","last_name":"{{Last Name}}","organization_name":"{{Company}}"}' \
  --with 'pdl=peopledatalabs_enrich_contact:{"first_name":"{{First Name}}","last_name":"{{Last Name}}","company":"{{Company}}"}' \
  --end-waterfall \
  --with 'verify=leadmagic_email_validation:{"email":"{{email}}"}'

deepline enrich --input contacts.csv --output verified.csv \
  --with 'verify=leadmagic_email_validation:{"email":"{{Email}}"}' \
  --with 'filter=run_javascript:"return row.verify_status === \"valid\" ? row : null"'

deepline enrich --input leads.csv --output scored.csv \
  --with 'company=crustdata_companydb_autocomplete:{"field":"company_name","query":"{{Company}}"}' \
  --with 'score=call_ai:{"prompt":"Score this lead 1-10 against our ICP (Series B+ SaaS, 50-500 employees, NA/EU). Company: {{company}}. Title: {{Title}}. Return JSON with score, tier (A/B/C), and reason.","json_mode":true}' \
  --rows 0:1  # pilot on 2 rows first

# Build company list + find contacts + enrich + validate
deepline enrich --input target-companies.csv --output tam.csv \
  --with 'company=crustdata_companydb_autocomplete:{"field":"company_name","query":"{{Company}}"}' \
  --with 'contacts=apollo_org_search:{"organization_name":"{{Company}}","person_titles":["VP Sales","Head of Revenue"]}' \
  --with-waterfall "email" \
  --with 'apollo_email=apollo_people_match:{"first_name":"{{contacts.first_name}}","last_name":"{{contacts.last_name}}"}' \
  --with 'pdl_email=peopledatalabs_enrich_contact:{"first_name":"{{contacts.first_name}}","last_name":"{{contacts.last_name}}"}' \
  --end-waterfall \
  --with 'verify=leadmagic_email_validation:{"email":"{{email}}"}' \
  --with 'score=call_ai:{"prompt":"Score 1-10 for ICP fit: {{company}} {{contacts}}","json_mode":true}'

# After enrichment, push top-scoring leads to sequencer
deepline sequence --provider instantly --campaign tam-q1 --input tam.csv

# Or push to multiple sequencers
deepline sequence --provider lemlist --campaign outbound-q1 --input tam.csv
deepline sequence --provider heyreach --campaign linkedin-q1 --input tam.csv

Agents write the pipeline, Deepline runs it

Deepline ships a Claude Code skill with slash commands for every enrichment workflow. Describe what you want in plain English — the agent reads the tool catalog, writes the pipeline, runs it, and reviews the output. Context from each step carries forward into the next.

> "I have a CSV of 200 leads from a conference. Enrich emails
>  with waterfall, validate them, score against our ICP, and
>  push the top 50 to Instantly."

# Claude Code reads the Deepline skill and runs:
deepline enrich --input conference.csv --output enriched.csv \
  --with-waterfall "email" \
  --with 'apollo=apollo_people_match:...' \
  --with 'pdl=peopledatalabs_enrich_contact:...' \
  --end-waterfall \
  --with 'verify=leadmagic_email_validation:...' \
  --with 'score=call_ai:...' \
  --rows 0:1  # pilot first

# Reviews results, then runs full batch + sequences:
deepline sequence --provider instantly --campaign conference-q1 --input enriched.csv

No copy-pasting commands. No reading docs. Works the same way with Codex and Cursor — any agent that can execute shell commands can orchestrate Deepline.

Why the CLI beats the spreadsheet

Common GTM engineer setups

Trusted by GTM teams

Frequently asked questions

Learn more

• Deepline vs Clay — full feature comparison
• What is waterfall enrichment?
• Deepline for Revenue Operations
• Install Deepline