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Issue Rivhit receipts from WhatsApp photos using Google Vision and GPT-4o

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Issue Rivhit receipts from WhatsApp photos using Google Vision and GPT-4o preview
Open on n8n.io

1. Workflow Overview

How it works 1. Courier sends an invoice photo to WhatsApp → AI extracts all details via Google Vision OCR 2. Courier sends a payment photo (check, bank transfer, credit card voucher) → AI matches ...

Best for

  • Invoice Processing automation workflows
  • AI Chatbot automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.if, n8n-nodes-base.code, n8n-nodes-base.httprequest, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.toolcode, @n8n/n8n-nodes-langchain.memorybufferwindow

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by achiya.

Original n8n.io source

1.1 Workflow description

Title
Issue Rivhit receipts from WhatsApp photos using Google Vision and GPT-4o
Workflow name
Issue Rivhit receipts from WhatsApp photos using Google Vision and GPT-4o

How it works

  1. Courier sends an invoice photo to WhatsApp → AI extracts all details via Google Vision OCR
  2. Courier sends a payment photo (check, bank transfer, credit card voucher) → AI matches it to the invoice
  3. AI presents a summary and asks for confirmation
  4. Once approved — receipt is created in Rivhit, invoice is closed, and the PDF is sent back to WhatsApp

Supports cash, checks, credit cards, bank transfers, and split payments. Includes automatic customer lookup by tax ID and Israeli bank code recognition.

Set up steps

Takes about 10 minutes:

  1. Set up a WAHA instance and point its webhook to this workflow
  2. Add your Google Cloud Vision API key to the HTTP Request node
  3. Add your Rivhit API token to the "api key" Set node
  4. Replace the WhatsApp group ID in the Filter node with yours
  5. Connect your OpenAI credentials
  6. Activate and start sending photos!

See the sticky notes inside the workflow for detailed instructions.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 2 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 3 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 4 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 5 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 6 - Sticky Note5

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 7 - Sticky Note6

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 8 - Sticky Note7

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 9 - Is there a picture or not?

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 10 - Preparing a message

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 11 - Extracting text from images

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 12 - api key

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 13 - AI Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3.1

Block 14 - rivhit_api

Type / Role
@n8n/n8n-nodes-langchain.toolCode - toolCode
Config choices
Version 1.3

Block 15 - Simple Memory

Type / Role
@n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices
Version 1.3

Block 16 - OpenAI Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.3

Block 17 - Separation between the message and document link

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 18 - Only if there is an attachment

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 19 - Send a file

Type / Role
@devlikeapro/n8n-nodes-waha.WAHA - WAHA
Config choices
Version 202502

Block 20 - Send a text message

Type / Role
n8n-nodes-waha.WAHA - WAHA
Config choices
Version 202411

Block 21 - Start Typing

Type / Role
@devlikeapro/n8n-nodes-waha.WAHA - WAHA
Config choices
Version 202502

Block 22 - Only if it's from the bot's group

Type / Role
n8n-nodes-base.filter - filter
Config choices
Version 2.3

Block 23 - Webhook

Type / Role
n8n-nodes-base.webhook - webhook
Config choices
Version 2.1

3. Summary Table

Workflow Issue Rivhit receipts from WhatsApp photos using Google Vision and GPT-4o
Complexity advanced
Nodes 23
Categories Invoice Processing, AI Chatbot
Author achiya
Published 15 Mar 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/14061/14061.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Issue Rivhit receipts from WhatsApp photos using Google Vision and GPT-4o do?

How it works 1. Courier sends an invoice photo to WhatsApp → AI extracts all details via Google Vision OCR 2. Courier sends a payment photo (check, bank transfer, credit card voucher) → AI matches ...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Invoice Processing, AI Chatbot use case.