Harvest → Klipfolio
AI-first ETL from Harvest into Klipfolio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Harvest into Klipfolio
Datrise syncs Harvest's time entries, projects, clients, invoices, and utilization 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
Harvest: Time tracking and project profitability for services teams.
Klipfolio: Dashboard platform for real-time KPIs and metric wallboards.
How Harvest entities map to Klipfolio
| Harvest entity | Klipfolio object | Notes |
|---|---|---|
| time entries | harvest_time_entries | id PK · custom fields → flattened columns for Klips |
| projects | harvest_projects | id PK · linked to harvest_time_entries |
| clients | harvest_clients | id PK · linked to harvest_time_entries |
| invoices | harvest_invoices | id PK · linked to harvest_time_entries |
FAQ
How does Datrise handle Harvest'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 Harvest to Klipfolio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or data feeds.
Related pipelines
More destinations for Harvest
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