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CRM ⇄ Database

Chorusai to Postgres Heroku integration — real-time, two-way sync

Keep Chorusai and Postgres Heroku 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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Why teams connect Chorusai and Postgres Heroku

Treat Chorusai like part of your database: its records live in Postgres Heroku 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 Postgres Heroku, where it can be queried and joined like everything else.

Stacksync mirrors Users, Trackers, Deals, Scorecards from Chorusai into Tables, Views, Materialized Views, Schemas in Postgres Heroku 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 Export Scorecards and their scores to a database to power rep-coaching and QA dashboards across sales teams.
  • 02 Read the Deals associated with each conversation to attribute call activity to open opportunities in a BI model.
  • 03 Expose CRM objects as Postgres tables the Heroku application can query and join directly
  • 04 Sync Heroku Postgres into a warehouse for reporting without running ETL dynos

Common sync patterns

Query the CRM like a database

Accounts, contacts, and custom objects from Chorusai become tables in Postgres Heroku you can join with application data directly.

Product events onto CRM records

Signup, usage, or lifecycle changes written to Postgres Heroku 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.

What you can sync between Chorusai and Postgres Heroku

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 Postgres Heroku objects How this pairing syncs
Moments Timestamped highlight clips from a conversation; created via the API to capture key call snippets. Follower Databases Heroku-managed read replicas usable as low-impact sync sources. Moments is specific to Chorusai and Follower Databases to Postgres Heroku — each maps to any object or custom field on the other side.
Playlists Curated collections of Moments and Recordings; created and managed to share coaching examples across teams. Tables Standard Postgres tables; the primary two-way sync target for app data. Playlists is specific to Chorusai and Tables to Postgres Heroku — each maps to any object or custom field on the other side.
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 Read-side projections exposed to outbound syncs. Engagements is specific to Chorusai and Views to Postgres Heroku — 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. Materialized Views Precomputed result sets synced outward on refresh. Recordings (Conversations) is specific to Chorusai and Materialized Views to Postgres Heroku — 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. Schemas Namespaces that scope which tables a sync reads and writes. Users is specific to Chorusai and Schemas to Postgres Heroku — 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. Primary and Unique Keys Match keys for idempotent upserts from connected systems. Trackers is specific to Chorusai and Primary and Unique Keys to Postgres Heroku — each maps to any object or custom field on the other side.

How changes propagate between Chorusai and Postgres Heroku

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 Postgres Heroku 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 Postgres Heroku as a row-level write, with types converted between the two schemas.

Postgres Heroku Chorusai Interval-based propagation

DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.

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.
  • Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with Chorusai ⇄ Postgres Heroku

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Chorusai or Postgres Heroku 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 Postgres Heroku record.

Observability

Monitoring

Track your Chorusai ⇄ Postgres Heroku 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 Postgres Heroku.

How the Chorusai and Postgres Heroku 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

Postgres Heroku

Integration surface
SQL wire protocol (standard PostgreSQL)
Authentication
Database credentials from the Heroku DATABASE_URL config var; SSL required
Change detection
Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
Capabilities
read · write
Rate limits
No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works

How to connect Chorusai to Postgres Heroku — 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 Postgres Heroku 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
    Postgres Heroku connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Chorusai and Postgres Heroku 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 ⇄ Postgres Heroku
    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 Postgres Heroku
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Chorusai and Postgres Heroku 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 469 integrations available for Chorusai and Postgres Heroku.

Popular · 7 of 469
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