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CRM ⇄ Database

Chorusai to Citus integration — real-time, two-way sync

Keep Chorusai 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.

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

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Why teams connect Chorusai and Citus

Treat Chorusai like part of your database: its records live in Citus as real tables, and writes in either place sync to the other in seconds.

Product and engineering teams constantly need CRM data, and the CRM API is a poor way to get it: rate limits, pagination, custom objects, and integration code that breaks when an admin renames a field. What they actually want is the data in Citus, where it can be queried and joined like everything else.

Stacksync mirrors Engagements, Recordings (Conversations), Users, Trackers from Chorusai into Sequences, Distributed tables, Reference tables, Local tables in Citus with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in Chorusai with validation intact. Go-to-market teams keep working in the CRM, engineers keep working in the database, and neither has to think about the other.

Common use cases

  • 01 Sync Trackers such as pricing, competitor, and next-steps mentions onto matching CRM Opportunities as coaching and deal-risk signals.
  • 02 Export Scorecards and their scores to a database to power rep-coaching and QA dashboards across sales teams.
  • 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

Product events onto CRM records

Signup, usage, or lifecycle changes written to Citus sync onto the matching records in Chorusai, giving go-to-market teams live product context.

Internal tools without API code

Back-office apps read and write the synced tables; Stacksync handles the Chorusai API, limits, and retries.

Trigger workflows from CRM changes

Field and stage updates in Chorusai arrive as row changes in Citus, ready to drive jobs and notifications.

What you can sync between Chorusai 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.

Chorusai objects Citus objects How this pairing syncs
Engagements Meetings and dialer calls, the core record; filterable by date_time, participants, and processing_state, and polled incrementally to read conversation activity out. Views Curated projections over distributed data, often used as read-only sync sources. Engagements is specific to Chorusai and Views to Citus — each maps to any object or custom field on the other side.
Recordings (Conversations) The recorded call with utterances, transcript, thumbnails, and metrics; read for analysis and uploaded or deleted through the API. Sequences Key generators that matter when external writes must not collide with application inserts. Recordings (Conversations) is specific to Chorusai and Sequences to Citus — each maps to any object or custom field on the other side.
Users Chorus users with roles and team membership; read to map engagement owners and participants to CRM and warehouse identities. Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. Users is specific to Chorusai and Distributed tables to Citus — each maps to any object or custom field on the other side.
Trackers AI keyword and topic trackers (pricing, competitors, next steps) surfaced within a conversation; read out as coaching and deal-risk signals. Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. Trackers is specific to Chorusai and Reference tables to Citus — each maps to any object or custom field on the other side.
Deals CRM opportunity context attached to a conversation (account, deal, owner); read to attribute call activity to open pipeline. Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. Deals is specific to Chorusai and Local tables to Citus — each maps to any object or custom field on the other side.
Scorecards Call QA and coaching assessments with reviewer, recipient, and scores; read and exported for rep-performance reporting. Schemas Standard Postgres namespaces used to scope what a sync user can read and write. Scorecards is specific to Chorusai and Schemas to Citus — each maps to any object or custom field on the other side.

How changes propagate between Chorusai 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.

Chorusai Citus Interval-based propagation

DetectionStacksync polls Chorusai for changes on an incremental schedule, reading only records changed since the previous pass. Polling the engagements endpoint on date_time and processing_state.

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

Citus Chorusai 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 Chorusai through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Chorusai: Rate limits are not publicly documented; recording upload and analysis are asynchronous, so transcripts and trackers appear only after processing_state completes.
What ships with Chorusai ⇄ Citus

Connect Chorusai and Citus for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Chorusai or Citus instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Chorusai 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 Chorusai or Citus record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Chorusai and Citus.

How the Chorusai and Citus connectors work

Chorusai

Integration surface
REST API (api-docs.chorus.ai)
Authentication
Per-user API token generated in Chorus Personal Settings, sent in the Authorization request header
Change detection
Polling the engagements endpoint on date_time and processing_state; no public change webhooks or CDC
Capabilities
read · write
Rate limits
Rate limits are not publicly documented; recording upload and analysis are asynchronous, so transcripts and trackers appear only after processing_state completes
Chorusai setup guide

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 Chorusai 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.

  1. 01

    Connect your apps

    Authenticate Chorusai 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Chorusai connected
    Citus connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Chorusai 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Chorusai ⇄ Citus
    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
    Chorusai Citus
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Chorusai and Citus 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 453 integrations available for Chorusai and Citus.

Popular · 6 of 453
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