Mercury ChatGPT

When settled transaction in Mercury, sync it to ChatGPT (OpenAI).

When a transaction settles in Mercury, send details to ChatGPT for categorization.

Try:

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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.

Mercury Explore Mercury →

Triggers
New expense submitted

Fires when an employee submits a new expense in Mercury.

Expense approved

Fires when an expense in Mercury is approved.

Expense rejected

Fires when an expense in Mercury is rejected.

Receipt uploaded

Fires when a receipt is attached to an expense in Mercury.

Actions
Create expense report

Creates a new expense report in Mercury.

Approve expense

Approves a pending expense in Mercury.

Reject expense

Rejects a pending expense in Mercury.

Sync to accounting

Syncs an approved expense in Mercury to the general ledger.

ChatGPT Explore ChatGPT →

Triggers
New conversation started

Fires when a new chat or conversation begins in ChatGPT.

Lead captured in chat

Fires when ChatGPT captures a lead during a conversation.

Conversation handed off

Fires when ChatGPT escalates a conversation to a human.

Actions
Send a message

Sends a message to a user through ChatGPT.

Generate an answer

Asks ChatGPT a question against its knowledge base and returns the answer.

Summarize a conversation

Uses ChatGPT to summarize a chat transcript.

Create a ticket from a chat

Opens a support ticket from an ChatGPT conversation.

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FAQ

Common questions

Can Knit build “When settled transaction in Mercury, sync it to ChatGPT (OpenAI).” between Mercury and ChatGPT?

Yes — describe it in the box above and Knit's Integrations Agent researches Mercury and ChatGPT'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.

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