Real-time
Two-way sync
Changes in Autopilot or Citus instantly reflect in both systems. No stale data, no manual imports.
AI ⇄ Database
Autopilot to Citus integration — real-time, two-way sync
Keep Autopilot and Citus in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Autopilot and Citus
Sync the records in Citus 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. Citus 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 Citus it describes are two halves of the same thing, and they drift the moment one is updated without the other.
Stacksync syncs Reference tables, Local tables, Schemas, Views in Citus with Activities, Contacts, Lists, Custom Fields in Autopilot in real time. Rows created or changed in Citus 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 Citus, 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 Citus 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 Add contacts to a Journey from a database event or CRM stage change to start automated onboarding or nurture sequences.
- 02 Mirror List and Smart Segment membership into a warehouse to power attribution and audience analytics alongside other sources.
- 03 Use a Citus cluster as the scalable operational store behind a customer-facing app while syncing summaries back to internal tools.
- 04 Consolidate per-tenant rows from distributed tables into per-customer reporting databases.
Common sync patterns
One record, one identifier
Each item in Autopilot carries the key of the row in Citus it came from, so results resolve back to the exact record with nothing orphaned or duplicated.
Run the AI on current data
Rows created or changed in Citus flow into Autopilot as they happen, so embeddings, classifications, and prompts run on the latest records instead of a nightly snapshot.
Write results back onto the record
Scores, labels, extracted fields, or generated text produced in Autopilot land on the matching row in Citus, next to the source data your applications already query.
What you can sync between Autopilot and Citus
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 | Citus objects | How this pairing syncs | |
|---|---|---|---|
| Lists Static contact lists; membership is readable per list and writable by adding or removing contacts. | Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Lists is specific to Autopilot and Distributed tables to Citus — 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. | Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Custom Fields is specific to Autopilot and Reference tables to Citus — 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. | Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Smart Segments is specific to Autopilot and Local tables to Citus — 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. | Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | Journeys (Triggers) is specific to Autopilot and Schemas to Citus — 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. | Views Curated projections over distributed data, often used as read-only sync sources. | Activities is specific to Autopilot and Views to Citus — each maps to any object or custom field on the other side. | |
| Contacts Core people records (email, name, custom fields, list and segment membership); upserted two-way as the primary sync object. | Sequences Key generators that matter when external writes must not collide with application inserts. | Contacts is specific to Autopilot and Sequences to Citus — each maps to any object or custom field on the other side. |
How changes propagate between Autopilot and Citus
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 Citus 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 Citus as a row-level write, with types converted between the two schemas.
Citus Autopilot Sub-second propagation
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
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.
What ships with Autopilot ⇄ Citus
Connect Autopilot and Citus for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Autopilot–Citus connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Autopilot or Citus 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 Citus record.
Observability
Monitoring
Track your Autopilot ⇄ Citus 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 Citus.
How the Autopilot and Citus 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.
Citus
- Integration surface
- PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node
- Authentication
- Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options)
- Change detection
- PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres
- Capabilities
- read · write · CDC
How it works
How to connect Autopilot to Citus — 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.
- 01
Connect your apps
Authenticate Autopilot and Citus with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Autopilot
connected
Citus
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Autopilot and Citus 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.
objects · Autopilot ⇄ CitusCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Autopilot CitusCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Autopilot and Citus integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Autopilot and Citus: authenticate both systems, choose the objects to sync (such as Autopilot's Lists and Custom Fields), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Autopilot and Citus: One record, one identifier; Run the AI on current data; Write results back onto the record. Each item in Autopilot carries the key of the row in Citus it came from, so results resolve back to the exact record with nothing orphaned or duplicated.
-
Autopilot: 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/. Citus: PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node. Authentication: Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options). Stacksync manages authentication, retries, and rate limits on both sides.
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Autopilot: There is no change-data-capture: incremental sync polls /contacts with bookmark cursor pagination on updated timestamps, and bulk writes are done by passing an array to the contact upsert endpoint. Citus: Distributed tables are sharded by a declared distribution column, and reference tables are fully replicated to all nodes; the table type changes how writes and joins behave. Stacksync's field mapping accounts for these differences between Autopilot and Citus without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Autopilot and Citus records are not retained after a sync operation.
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 405 integrations available for Autopilot and Citus.
Popular · 7 of 405
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Autopilot ⇄ Dynamo DB -
Autopilot ⇄ IBM Db2 -
Autopilot ⇄ Firebase -
Autopilot ⇄ SingleStore -
Citus ⇄ Pinecone -
Citus ⇄ Openai -
Citus ⇄ Azure OpenAI
No integrations match .
