CI/CD for Revenue · CRM
Gate CRM data before it ships downstream
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 CRM gate work?
Same engine, different adapter. CRM objects (contacts, pipelines, routing rules) carry their own type-specific checks: field completeness, routing logic validation, lead-score 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
CRM intelligence, not just field validation.
The gate runs the checks. The intelligence layer finds the patterns. Data quality, routing drift, pipeline context, all surfaced before bad data flows downstream.
Data Quality Intelligence
Auto-detect decay patterns: personal emails that should be business, stale company fields from prior employers, duplicates across import batches. Catch it before it contaminates the pipeline.
Routing Drift Detection
When routing rules change, the gate checks for coverage gaps, circular fallbacks, and capacity violations. Surface the downstream impact before it routes real leads into a void.
Pipeline Context
Surfaces data quality patterns across imports and syncs: which sources produce the most rejects, where field completeness drops, what enrichment paths reduce false positives.
Agent-Ready Data
Expose data quality verdicts and dedup intelligence to CRM agents via MCP. Agents enrich, validate, and route contacts autonomously with gate-verified data.
If this is your week, you care a lot
- ✗CRM data decays silently and nobody catches it until a pipeline review
- ✗Routing rules change and the downstream impact is discovered weeks later
- ✗Lead scoring models go stale as the market shifts, producing false positives
- ✗Field validation is manual or missing entirely, so bad data flows everywhere
What the gate gives you
- One five-severity verdict on every CRM object before bad data ships downstream
- Policy-based checks on data completeness, routing accuracy, and field validity
- Same deterministic gate whether data was entered by a rep, synced, or auto-enriched
- The same Object/Policy/Test/Issue loop that runs on content, extended to CRM data quality
How the loop runs on CRM
Same nine-step loop as content. Different adapter, different checks, same verdict.
Scenario
A batch of 500 new contacts synced from a webinar registration form into HubSpot
Object
Each contact record ingested as an object with company, title, email, and enrichment fields
Policy
Policy requires: valid business email, company field populated, no duplicates in existing database, title matches ICP
Test
Email validity check, field completeness check, dedup scan against existing contacts, ICP title match
Issue
FAIL: '127 contacts have personal email domains (gmail, yahoo). 23 are duplicates of existing records'
Fix
Ops enriches personal emails via Prospeo, merges 23 duplicates. Fix recorded per contact
Verify
Re-test confirms all emails are business domains, zero duplicates, field completeness at 100%
Deploy
Clean contacts synced to HubSpot with proper lifecycle stage and lead source
Monitor
Monthly data quality scan flags contacts with changed companies or bounced emails
dokeo test webinar-batch-aug → PASS (email-valid ✓ dedup ✓ completeness 100% icp-match 89%) → ready to sync
dokeo test webinar-batch-aug → FAIL (127 personal emails, 23 duplicates, 45 missing company field) → blocked
Status: Coming (HubSpot adapter built)
The CRM domain has 8 registered object types and 4 check functions. The HubSpot adapter is built, pending OAuth credentials.
Same intelligence layer. Different adapter.
Content proves the loop works. CRM data quality connects next.