DatriseAI-first ETL

Wise Agent Mode

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

How Datrise loads Wise Agent into Mode

Datrise syncs Wise Agent'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

Wise Agent: Real estate CRM for leads, listings, and agent follow-up.

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

How Wise Agent entities map to Mode

Wise Agent entityMode objectNotes
contactswise_agent_contactsid PK · custom fields → flattened columns for SQL and notebooks
accountswise_agent_accountsid PK · linked to wise_agent_contacts
dealswise_agent_dealsid PK · linked to wise_agent_contacts
activitieswise_agent_activitiestemporal columns events

FAQ

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

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

Related pipelines

Early access

Connect Wise Agent 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.