DatriseAI-first ETL

Agendor Mode

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

How Datrise loads Agendor into Mode

Datrise syncs Agendor's contacts, accounts, deals, activities, and lifecycle events 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

Agendor: CRM widely used in Latin America for sales pipeline and customer ops.

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

How Agendor entities map to Mode

Agendor entityMode objectNotes
contactsagendor_contactsid PK · custom fields → flattened columns for SQL and notebooks
accountsagendor_accountsid PK · linked to agendor_contacts
dealsagendor_dealsid PK · linked to agendor_contacts
activitiesagendor_activitiestemporal columns events

FAQ

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

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

Related pipelines

Early access

Connect Agendor 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.