DatriseAI-first ETL

Salesflare Mode

AI-first ETL from Salesflare into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Salesflare into Mode

Datrise syncs Salesflare's B2B account intelligence, interactions, and automated relationship timelines 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

Salesflare: B2B CRM focused on automation and relationship timeline data.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Salesflare entities map to Mode

Salesflare entityMode objectNotes
B2B account intelligencesalesflare_b2b_account_intelligenceid PK · custom fields → flattened columns for SQL and notebooks
interactionssalesflare_interactionsid PK · linked to salesflare_b2b_account_intelligence
automated relationship timelinessalesflare_automated_relationship_timelinestemporal columns events

FAQ

How does Datrise handle Salesflare'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 Salesflare to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

Connect Salesflare to Mode the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.