Features

Find verified work emails and phone numbers.

Use Deepline to find verified work emails and phone numbers with waterfall enrichment, validation gates, and agent-native execution.

Deepline
30+
providers across the Deepline stack
4
sequencers supported downstream
1
agent-native workflow instead of tab juggling

What This Page Is About

Verified business contact data, not generic lead fluff

The job is not to produce more rows. The job is to produce contact data you can actually use.

That means:

  • verified work emails,
  • direct dials or mobile numbers when available,
  • clear provenance through the workflow,
  • and a clean handoff into the next system.

If a row cannot be resolved safely, Deepline should return null and move on. That is a feature, not a flaw.

How It Works

One workflow from input to sequencer-ready output

Input: Name + company, LinkedIn URL, or company + role
Choose the right waterfall
input-aware routing
Found? Stop.
No result? Try next
Find the work email
multi-provider lookup
Found? Stop.
No result? Try next
Validate the result
gate risky rows before send
Found? Stop.
No result? Try next
Look up phone data
add direct dial or mobile when available
Found? Stop.
No result? Try next
Push downstream
route only qualified records
Found? Stop.
Output: Validated contact record ready for activation

Primitives

What the feature actually includes

AttributeValueDetail
Primary outputsWork email, phone, LinkedIn, company contextPhone coverage depends on provider and region
Execution styleWaterfall + validationStops on the first valid result instead of spraying providers
Workflow surfacesCLI, API, coding agentsBuilt for Claude Code, Codex, and other terminal-first agents
Downstream systemsInstantly, Lemlist, Smartlead, HeyReachRoute qualified contacts after validation
Provider modelBYOK or managed creditsUse your own provider accounts or managed execution
Failure behaviorNull instead of fabricated dataA miss is reported as a miss

Use Cases

Where teams use this

Outbound prospecting

Start with accounts or target personas. Resolve verified work emails first. Add phone numbers when the motion justifies it. Then push only the qualified rows into a sequencer.

CRM repair

Re-verify stale emails, recover missing work data, and block dead addresses before they hurt sender reputation.

Agent-led research

Combine web signals, company context, and contact resolution in the same environment instead of exporting data between tools.

Compliance

The compliance posture is operational, not hand-wavy

Deepline is built around auditable steps:

  • use provider APIs where possible,
  • use purpose-built actors for surfaces like LinkedIn,
  • keep validation in the workflow,
  • and avoid claiming a contact exists when no provider can resolve it.

This does not remove the need for legal review, consent policies, or regional compliance decisions. It does mean the system behaves like a professional data workflow instead of a black-box growth hack.

One subtle but important product choice: Deepline treats LinkedIn scraping and public-site crawling as different problems. That is the right tradeoff for accuracy, reliability, and operator clarity.

CLI Example

A simple way to think about the workflow

deepline enrich --input accounts.csv --output contacts.csv \
  --waterfall \
  --providers apollo,leadmagic,prospeo

The exact play depends on your input shape, but the principle stays the same: resolve the best business contact, validate it, and only then move the row forward.

FAQ

Frequently asked questions

What inputs does Deepline need to find work emails?+

The strongest inputs are name plus company plus domain. Deepline also supports workflows that start from LinkedIn URLs, company plus role, or existing email addresses for reverse enrichment.

Can Deepline find phone numbers too?+

Yes. Deepline supports phone lookup workflows where provider coverage allows it. Phone coverage is usually lower and more region-sensitive than email coverage, so the workflow should treat phone as an additional field, not a guaranteed output.

How does Deepline reduce bad contact data?+

By validating results inside the workflow, stopping waterfalls on the first valid hit, and returning null when no safe result exists. Deepline does not invent data to make the row look complete.

Is this compliant for GTM teams?+

Deepline is designed around provider APIs, actor-based integrations, and explicit workflow steps rather than UI-only hacks. Teams still need to respect local laws, consent requirements, and provider terms for their own use case, but the product is built for auditable execution rather than black-box scraping magic.

Why not just buy one all-in-one contact database?+

Because no single provider wins everywhere. Work emails, mobile numbers, and firmographic context often come from different sources. Waterfall enrichment increases the chance of getting a valid business contact without locking you to one vendor's blind spots.

Related

Keep reading

Related

Resolve contact data inside one workflow

Find, validate, enrich, and route work emails and phone numbers without breaking the agent flow.