What is Data Orchestration?
Definition: The coordination of multiple data sources, enrichment steps, and transformation logic into a single automated workflow that produces clean, actionable contact and account records.
Data orchestration is what Clay does. You don't just look up one data point. You chain together 5, 10, 20 enrichment and transformation steps into a pipeline that takes a raw list of companies and produces a fully qualified outbound list.
A typical orchestration workflow: Start with a list of companies. Enrich with Clearbit for firmographics. Filter by employee count (50-500) and industry (SaaS). Find VP-level contacts via Apollo. Verify emails through FullEnrich. Score leads using an LLM prompt that reads their LinkedIn bio and recent company news. Push qualified leads to HubSpot. Enroll in an Instantly sequence. All of this runs without manual intervention.
Before Clay, GTM Engineers built this logic in n8n, Make, or custom Python scripts. Those approaches still work and give you more flexibility, but they require more engineering skill. Clay made orchestration visual and accessible to non-engineers.
The key distinction from simple enrichment: orchestration includes logic. If-then branching, score thresholds, provider fallbacks, data transformation, and output routing. It's the difference between looking up a phone number and building an entire pipeline from prospect identification to sequence enrollment.