DatriseAI-first ETL

Intercom Neon

AI-first ETL from Intercom into Neon. Governed entities, incremental sync, typed landing tables.

How Datrise loads Intercom into Neon

Datrise syncs Intercom's conversations, customer attributes, inbox events, and support engagement into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

Intercom: Customer messaging platform with CRM-style account and conversation context.

Neon: Serverless Postgres destination with branching and autoscaling.

How Intercom entities map to Neon

Intercom entityNeon objectNotes
conversationsintercom_conversationsid PK · custom fields → jsonb columns
customer attributesintercom_customer_attributesid PK · linked to intercom_conversations
inbox eventsintercom_inbox_eventstimestamptz events
support engagementintercom_support_engagementid PK · linked to intercom_conversations

FAQ

How does Datrise handle Intercom's custom fields in Neon?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Neon types.

How does the Intercom to Neon sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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