DatriseAI-first ETL

Clay to Klipfolio Integration

AI-first ETL from Clay into Klipfolio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Clay into Klipfolio

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists into Klipfolio as query-ready tables or feeds Klipfolio reads. Flexible or custom fields land in flattened columns for Klips, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or data feeds, so re-runs update only what changed. Date-partitioned facts for trend Klips. Klipfolio pulls from sources on a refresh interval, so Datrise keeps tables incrementally current to match.

Ideal for real-time KPI dashboards and wallboards.

Endpoints

Clay: Data enrichment tables that build outbound lists.

Klipfolio: Dashboard platform for real-time KPIs and metric wallboards.

How Clay entities map to Klipfolio

Clay entityKlipfolio objectNotes
tablesclay_tablesid PK · custom fields → flattened columns for Klips
rowsclay_rowsid PK · linked to clay_tables
enrichment runsclay_enrichment_runsid PK · linked to clay_tables
waterfallsclay_waterfallsid PK · linked to clay_tables

FAQ

How does Datrise handle Clay's custom fields in Klipfolio?

Flexible values are stored as flattened columns for Klips, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Klipfolio types.

How does the Clay to Klipfolio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or data feeds.

Related pipelines

Early access

Connect Clay to Klipfolio the easy way

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