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AI ⇄ Database

Autopilot to PostgreSQL integration — real-time, two-way sync

Keep Autopilot and PostgreSQL in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Autopilot and PostgreSQL

Sync the records in PostgreSQL into Autopilot and land its embeddings, classifications, and generated fields back on the same rows, in real time and without a pipeline to maintain.

AI systems do not hold customers or invoices the way business apps do. What they hold is derived from your data: the vectors and metadata in a vector store, or the classifications, extracted fields, and generated text a model produces over records it was given. PostgreSQL is where those source records actually live. The bridge between the two is the row itself, since an item in Autopilot and the record in PostgreSQL it describes are two halves of the same thing, and they drift the moment one is updated without the other.

Stacksync syncs Tables, Views, Materialized Views, Schemas in PostgreSQL with Lists, Custom Fields, Smart Segments, Journeys (Triggers) in Autopilot in real time. Rows created or changed in PostgreSQL flow into Autopilot so inference and embedding run on current data, and the scores, labels, and generated fields Autopilot produces flow back onto the matching rows in PostgreSQL, mapped field by field. A change on either side appears on the other within seconds, with no extraction job or webhook plumbing to keep alive.

Because matching is by a stable identifier, every row in PostgreSQL stays tied to its AI-side counterpart in Autopilot. Retrieval, enrichment, and generated content always resolve back to the record they came from, so there are no orphaned vectors and no labels describing a version of a row that no longer exists.

Common use cases

  • 01 Stream Activities into a warehouse so opens, clicks, and journey steps sit next to product and revenue data for lifecycle reporting.
  • 02 Upsert Contacts from a CRM or product database into Autopilot so new signups and profile changes flow into email and SMS journeys without manual CSV imports.
  • 03 Let an application write to its own database and have those rows appear as records in business systems in near real time
  • 04 Consolidate data from several microservice databases into one operational Postgres store

Common sync patterns

Keep derived data fresh as sources change

When a row in PostgreSQL is updated or removed, its counterpart in Autopilot is updated or removed too, so nothing in Autopilot describes a record that has since changed or gone.

Backfill once, then stay in step

Load your existing rows from PostgreSQL into Autopilot to build the index or enrichment set, then let ongoing changes sync automatically instead of re-running the whole job.

One record, one identifier

Each item in Autopilot carries the key of the row in PostgreSQL it came from, so results resolve back to the exact record with nothing orphaned or duplicated.

What you can sync between Autopilot and PostgreSQL

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Autopilot objects PostgreSQL objects How this pairing syncs
Contacts Core people records (email, name, custom fields, list and segment membership); upserted two-way as the primary sync object. Tables The primary sync target; rows map one-to-one to records in connected SaaS systems. Contacts is specific to Autopilot and Tables to PostgreSQL — each maps to any object or custom field on the other side.
Lists Static contact lists; membership is readable per list and writable by adding or removing contacts. Views Read-side projections used to expose joined or filtered data to a sync. Lists is specific to Autopilot and Views to PostgreSQL — each maps to any object or custom field on the other side.
Custom Fields User-defined contact properties (string, number, date, boolean); discovered so field keys map cleanly to destination columns. Materialized Views Precomputed result sets synced outward on a refresh schedule. Custom Fields is specific to Autopilot and Materialized Views to PostgreSQL — each maps to any object or custom field on the other side.
Smart Segments Rule-based dynamic audiences; membership is computed by Autopilot, so it is read-only over the API. Schemas Namespaces that scope which tables a sync reads and writes. Smart Segments is specific to Autopilot and Schemas to PostgreSQL — each maps to any object or custom field on the other side.
Journeys (Triggers) Automation journeys; a contact can be added to a journey via its trigger endpoint to start automated email or SMS sequences. Columns Field-level mapping targets; types are mapped to the connected system's field types. Journeys (Triggers) is specific to Autopilot and Columns to PostgreSQL — each maps to any object or custom field on the other side.
Activities Per-contact activity and event history (opens, clicks, journey steps); read-only feed used for engagement reporting. Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. Activities is specific to Autopilot and Primary and Unique Keys to PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between Autopilot and PostgreSQL

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Autopilot PostgreSQL Interval-based propagation

DetectionStacksync polls Autopilot for changes on an incremental schedule, reading only records changed since the previous pass. No CDC.

DeliveryEach detected change is applied to PostgreSQL as a row-level write, with types converted between the two schemas.

PostgreSQL Autopilot Sub-second propagation

DetectionChanges in PostgreSQL are captured at the source via change data capture — no polling loop against its API. Logical replication (wal_level = logical) for change data capture via the "Postgres" connector.

DeliveryEach detected change is written to Autopilot through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Autopilot: The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
  • PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
What ships with Autopilot ⇄ PostgreSQL

Connect Autopilot and PostgreSQL for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Autopilot–PostgreSQL connection.

Real-time

Two-way sync

Changes in Autopilot or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Autopilot or PostgreSQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Autopilot or PostgreSQL record.

Observability

Monitoring

Track your Autopilot ⇄ PostgreSQL sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Autopilot and PostgreSQL.

How the Autopilot and PostgreSQL connectors work

Autopilot

Integration surface
REST API (Autopilot v1); Autopilot rebranded to Ortto in 2021 and the newer Ortto API co-exists with the legacy Autopilot endpoints
Authentication
Per-account API key sent in the autopilotapikey request header (generated in account settings); requests use Content-Type application/json against https://api2.autopilothq.com/v1/
Change detection
No CDC; incremental sync polls the /contacts endpoint with bookmark cursor pagination and updated timestamps. Journey webhook actions can push specific contact events, but there is no general change-subscription webhook, so polling is the reliable path.
Capabilities
read · write
Rate limits
The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
Autopilot setup guide

PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL frontend/backend protocol)
Authentication
Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
Change detection
Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
PostgreSQL setup guide
How it works

How to connect Autopilot to PostgreSQL — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Autopilot and PostgreSQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Autopilot connected
    PostgreSQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Autopilot and PostgreSQL objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Autopilot ⇄ PostgreSQL
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Autopilot PostgreSQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Autopilot and PostgreSQL integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

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SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 518 integrations available for Autopilot and PostgreSQL.

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