Salesloft → Mode
AI-first ETL from Salesloft into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Salesloft into Mode
Datrise syncs Salesloft's cadence activity, conversation signals, and revenue workflow execution into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
Salesloft: Revenue workflow platform for cadences, conversations, and coaching signals.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Salesloft entities map to Mode
| Salesloft entity | Mode object | Notes |
|---|---|---|
| cadence activity | salesloft_cadence_activity | temporal columns events |
| conversation signals | salesloft_conversation_signals | id PK · linked to salesloft_cadence_activity |
| revenue workflow execution | salesloft_revenue_workflow_execution | id PK · linked to salesloft_cadence_activity |
FAQ
How does Datrise handle Salesloft's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the Salesloft to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for Salesloft
Early access
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