Log new support tickets directly into database tables

When a customer submits a new ticket in Kayako, instantly insert a record into PostgreSQL to preserve central activity logs.

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How Knit builds this workflow

The Agent researches both APIs and wires the trigger on one side to the action on the other — no pre-built connector required. Here is the vocabulary it has to work with.

PostgreSQL Explore PostgreSQL →

Triggers

New row inserted

Fires when a new row is added to a table in PostgreSQL.

Row updated

Fires when an existing row changes in PostgreSQL.

Query result ready

Fires when a scheduled query in PostgreSQL finishes running.

Actions

Run a query

Runs a SQL query against PostgreSQL and returns the result.

Insert or update a row

Writes a new or updated row to PostgreSQL.

Sync a table

Syncs a table in PostgreSQL with data from another source.

Kayako Explore Kayako →

Triggers

New ticket created

Fires when a new support ticket is created in Kayako.

Ticket status changed

Fires when a ticket's status changes in Kayako.

Ticket assigned

Fires when a ticket in Kayako is assigned to an agent.

SLA breached

Fires when a ticket in Kayako breaches its response SLA.

Actions

Create ticket

Creates a new ticket in Kayako.

Update ticket status

Updates a ticket's status in Kayako.

Assign ticket

Assigns a ticket in Kayako to an agent.

Add ticket comment

Posts an internal or public comment on a ticket in Kayako.

Update ticket status when backend database state changes When an issue or order status row is updated in PostgreSQL, automatically adjust the related ticket status in Kayako. See details

Record SLA breaches in reporting database tables Whenever a ticket breaches its SLA in Kayako, insert an event row in PostgreSQL to track team compliance metrics over time. See details

See all PostgreSQL + Kayako integrations → · Browse the full workflow library →

Enterprise-grade security

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FAQ

Common questions

Can Knit build “Log new support tickets directly into database tables” between PostgreSQL and Kayako?

Yes — describe it in the box above and Knit's Integrations Agent researches PostgreSQL and Kayako's public API docs (or your own uploaded docs) and builds a working workflow, whether or not either app already has a pre-built connector.

How long does it take to build?

Minutes to a first working version, not weeks — you test it against real data before it goes anywhere near production.

What's the most common Databases & Warehouses + Ticketing automation?

Writing new and updated tickets from Kayako into a table in PostgreSQL continuously, so support metrics stay current without a manual export.

Does this capture custom fields and tags, or just the basics?

The Agent maps whatever custom fields and tags Kayako exposes, not just the default ticket schema, into the matching columns in PostgreSQL.