Clay is a spreadsheet. Deepline is a command.

The real difference

Your workflow is a command, not a spreadsheet

In Clay, a waterfall enrichment workflow means 15 formula columns, manual fallback logic, and a UI that crashes on large tables. In Deepline, the same workflow is one shell command: version-controlled, reproducible, shareable across clients, and runnable by your agent.

# Deepline: one command replaces 15 Clay formula columns
deepline enrich --input leads.csv --output enriched.csv \
--with-waterfall "email" \
--with '{"alias":"apollo","tool":"apollo_people_match","payload":{"first_name":"{{First Name}}","last_name":"{{Last Name}}"}}' \
--with '{"alias":"pdl","tool":"peopledatalabs_enrich_contact","payload":{"first_name":"{{First Name}}","last_name":"{{Last Name}}"}}' \
--end-waterfall \
--with '{"alias":"verify","tool":"leadmagic_email_validation","payload":{"email":"{{email}}"}}' \
--with '{"alias":"score","tool":"deeplineagent","payload":{"prompt":"Score this lead against our ICP","json_mode":true}}'

# Pilot on 2 rows before committing credits:

deepline enrich --input leads.csv --rows 0:1 --with-waterfall "email" ...

Workflow layer

Your GTM process becomes code

Price changes. Architecture lasts longer. The main Deepline bet is that GTM work should be executable: an SDK call, an API request, a CLI command, a scheduled job, or an agent step that writes back to your database.

BYOK mode has no Deepline platform fee for provider access. You pay providers directly for their data. Deepline still meters compute when your workflow uses data processing, agents, or web workers. Managed runs show estimates before paid provider calls.

Callout

Who should use what

Choose the right fit

Side-by-side

Feature comparison

Key difference

The agent gap

Clay was built around humans working in a browser. It has API surfaces, but the product center is still the workspace. Claude Code, Codex, and other AI coding agents fit better when the workflow is already an SDK call, API request, command, or database write.

Deepline exposes GTM work as code. An agent can call the SDK, hit the API, run deepline enrich, or inspect database output. Structured inputs, structured outputs.

# An agent can do this in Claude Code:
/deepline-gtm find verified work emails for leads.csv using waterfall enrichment

# Or with the CLI directly:

deepline enrich --input leads.csv \
--with '{"alias":"email","tool":"name_and_domain_to_email_waterfall","payload":{"first_name":"{{First Name}}","last_name":"{{Last Name}}","domain":"{{Domain}}"}}'

# Then push to your sequencer:

deepline tools execute instantly_add_to_campaign \
--payload '{"campaign_id":"abc-123","leads":[{"email":"{{email}}","first_name":"{{First Name}}"}]}'

# Clay has no equivalent CLI command

Scale

Row limits: the 50K cap

Clay's standard tables cap at 50,000 rows per table, even on Enterprise. Enterprise customers can enable "Passthrough Tables" for unlimited rows, but those work on a rolling basis, automatically deleting older rows. Not the same as truly unlimited storage.

Deepline is CSV-native. Your row limit is your disk space. Process 500K rows with the same command as 500.

Plans

Pricing is not the whole comparison

Compare current pricing before you buy. Clay can lower prices, Deepline can change rates, and provider costs move. The bigger question is where your GTM process lives.

Common questions

FAQ