CI/CD for Revenue · GTM

Gate outreach before it hits the market

The same intelligence layer that gates content, applied to outreach sequences, ICP definitions, battle cards, and launch plans.

Dokeo is CI/CD for Revenue: every scan runs the same deterministic checks used in production, across all 17 supported content types, with no black-box review.

How does the GTM gate work?

Same engine, different adapter. GTM objects (sequences, ICP docs, battle cards) carry their own type-specific checks: prospect-message fit, positioning consistency, data freshness. The five-severity verdict and the Object/Policy/Test/Issue loop are identical.

  • The same draft always returns the same verdict, safe to block a CI pipeline on.
  • Every FAIL names the specific check that failed and why.
  • 100 free scans a month, no credit card, same gate as production.

Intelligence layer

GTM intelligence, not just a checklist.

The gate runs the checks. The intelligence layer finds the patterns. Sequence quality, ICP drift, pipeline context, all surfaced before work reaches the market.

Sequence Intelligence

Auto-analyze personalization depth, spam trigger density, and deliverability signals across every step of your outreach. The gate catches what manual review misses at scale.

ICP Drift Detection

Compare targeting criteria across sequences, campaigns, and teams. Surface misalignment before it reaches the market, not in a quarterly review.

Pipeline Context

Surfaces patterns in what sequences convert versus what the gate flags. Connects quality signals to pipeline outcomes so the loop compounds.

Agent-Ready Data

Expose gate verdicts, failure patterns, and sequence intelligence to GTM agents via MCP. Agents scan sequences and act on issues autonomously.

If this is your week, you care a lot

  • Outreach sequences ship to thousands of prospects without a quality check
  • ICP definitions drift across teams and nobody catches the misalignment
  • Battle cards go stale the moment competitive intel changes
  • Launch plans get approved on vibes, not verified against a testable policy

What the gate gives you

  • One five-severity verdict on every GTM object before it reaches the market
  • Policy-based checks on sequence quality, ICP consistency, and positioning accuracy
  • Same deterministic gate whether sequences were built by a GTM engineer, SDR, or LLM
  • The same Object/Policy/Test/Issue loop that runs on content, extended to go-to-market

How the loop runs on GTM

Same nine-step loop as content. Different adapter, different checks, same verdict.

Scenario

An outreach sequence targeting a new ICP segment, built by a GTM engineer

1

Object

3-step email sequence + ICP definition + target list ingested as linked objects

2

Policy

Policy requires: personalization token in every step, no banned phrases, ICP-to-sequence alignment, deliverability checks

3

Test

Sequence quality check, ICP consistency check, spam-trigger scan, personalization coverage

4

Issue

FAIL: 'Step 2 has no personalization token, generic template will underperform' with the exact line flagged

5

Fix

GTM engineer adds {{company_recent_news}} merge field to step 2. Fix recorded

6

Verify

Re-test confirms personalization in all steps, ICP alignment passes. All policies clear

7

Deploy

Sequence pushed to Smartlead/HeyReach via webhook. Deployment record created

8

Monitor

Reply rate tracked per step. If step 2 reply rate drops below threshold, sequence reopens

PASSShips

dokeo test outreach-icp-fintech → PASS (personalization ✓ icp-match ✓ deliverability ✓) → ready to send

FAILBlocked

dokeo test outreach-icp-fintech → FAIL (step 2: no personalization, spam score 6.2/10) → blocked

Status: Coming

The GTM domain has 7 registered object types and 4 check functions. No test adapter or customer is connected yet. The in-app workspace shows exactly that: connect a data source, configure a policy, run the first test.

Same intelligence layer. Different adapter.

Content proves the loop works. GTM connects next. If you want early access to the GTM gate and its intelligence layer, let us know.