Zendesk ticket summarizer with Pinecone, OpenAI, and Slack

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Zendesk Ticket Summarizer with Pinecone, OpenAI, and Slack This workflow automates the process of summarizing recent Zendesk support tickets and sharing key insights in a Slack channel. It is ideal...

Best for

Ticket Management automation workflows
AI RAG automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.vectorstorepinecone, @n8n/n8n-nodes-langchain.embeddingsopenai, n8n-nodes-base.slack, @n8n/n8n-nodes-langchain.documentdefaultdataloader, n8n-nodes-base.wait, n8n-nodes-base.scheduletrigger, n8n-nodes-base.zendesk

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Zendesk ticket summarizer with Pinecone, OpenAI, and Slack
Workflow name: Zendesk ticket summarizer with Pinecone, OpenAI, and Slack

Zendesk Ticket Summarizer with Pinecone, OpenAI, and Slack

This workflow automates the process of summarizing recent Zendesk support tickets and sharing key insights in a Slack channel. It is ideal for support teams who want daily, AI-generated overviews of customer issues without manually reviewing each ticket.

How it works

Daily Trigger: The workflow runs every day at 10am.
Fetch Tickets: It retrieves all Zendesk tickets created in the last 24 hours (optionally filtered by brand).
Vector Storage: Tickets are stored in a Pinecone vector database, with relevant fields and metadata.
AI Summarization: An AI agent (using OpenAI) analyzes the tickets, identifies main complaints, and counts how many tickets mention each issue.
Slack Notification: The summary is posted to a specified Slack channel for your team to review.

Setup Instructions

Configure your Zendesk, Pinecone, OpenAI, and Slack credentials in the respective nodes.
Set your Pinecone index and namespace in both Pinecone nodes.
Adjust the Zendesk query if you want to filter by a specific brand.
Set the Slack channel ID where you want to receive the summaries.

Use case Get daily, actionable insights from your Zendesk tickets, helping your team quickly spot trends and recurring issues.

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 - OpenAI Chat Model1

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 2 - Pinecone Vector Store2

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

Block 3 - Embeddings OpenAI2

Type / Role: @n8n/n8n-nodes-langchain.embeddingsOpenAi - embeddingsOpenAi
Config choices: Version 1.2

Block 4 - Send to Slack channel

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

Block 5 - Default Data Loader1

Type / Role: @n8n/n8n-nodes-langchain.documentDefaultDataLoader - documentDefaultDataLoader
Config choices: Version 1.1

Block 6 - Wait1

Type / Role: n8n-nodes-base.wait - wait
Config choices: Version 1.1

Block 7 - Daily trigger

Type / Role: n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices: Version 1.2

Block 8 - Get tickets

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

Block 9 - Pinecone Vector Store - Tickets

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

Block 10 - Embeddings OpenAI

Type / Role: @n8n/n8n-nodes-langchain.embeddingsOpenAi - embeddingsOpenAi
Config choices: Version 1.2

Block 11 - AI Agent - Summary generator

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2

Block 12 - Sticky Note

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

Block 13 - Sticky Note1

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

Block 14 - Sticky Note2

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

Block 15 - Sticky Note3

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

Block 16 - Sticky Note4

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

Block 17 - Sticky Note5

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

Block 18 - Sticky Note6

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

3. Summary Table

Workflow	Zendesk ticket summarizer with Pinecone, OpenAI, and Slack
Complexity	advanced
Nodes	18
Categories	Ticket Management, AI RAG
Author	Ertay Kaya
Published	03 Nov 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/10484/10484.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

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

Download workflow JSON Original n8n.io source Ticket Management workflows AI RAG workflows

Frequently asked questions

What does Zendesk ticket summarizer with Pinecone, OpenAI, and Slack do?

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 Ticket Management, AI RAG use case.

Ertay Kaya

8 workflows

Nodes

@n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.vectorstorepinecone @n8n/n8n-nodes-langchain.embeddingsopenai n8n-nodes-base.slack @n8n/n8n-nodes-langchain.documentdefaultdataloader n8n-nodes-base.wait n8n-nodes-base.scheduletrigger n8n-nodes-base.zendesk

Complexity

advanced

Published 03 Nov 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/10484/10484.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Track post-therapy wellness with GPT-4o-mini, Telegram, Slack and Sheets

## Quick Overview This workflow uses Google Sheets, OpenAI, Telegram, and Slack to send post-therapy check-in messages, analyze patient replies for sentiment and risk, alert therapists to at-risk responses, and log non-urgent replies for ongoing wellness tracking. ## How it works 1. Runs every hour on a schedule trigger. 2. Reads session records from Google Sheets and keeps only sessions that have a session date and have not been marked as check-in sent. 3. Uses OpenAI (gpt-4o-mini) to generate a personalized, non-clinical Telegram check-in message from the patient’s session details. 4. Sends the check-in to the patient via Telegram and updates the Google Sheets session row to store the message and mark the check-in as sent. 5. Triggers on incoming Telegram messages, looks up the patient in a Google Sheets master list by Telegram ID, and selects the most relevant recent session to provide context. 6. Sends the patient reply and session context to OpenAI for JSON-formatted sentiment classification and parses the result into structured fields. 7. If the sentiment is classified as at-risk, posts an urgent alert to a Slack channel; otherwise, appends the reply and sentiment details to a Google Sheets wellness log. ## Setup 1. Connect Google Sheets OAuth credentials and update the spreadsheet document ID and sheet names for Sessions, Patients_Master, and Wellness_Log. 2. Create and connect a Telegram bot credential, set up the Telegram trigger webhook, and ensure patient Telegram chat IDs are stored in Google Sheets. 3. Add an OpenAI API key credential and confirm the selected model (gpt-4o-mini) meets your requirements. 4. Connect Slack OAuth credentials and replace the placeholder Slack channel ID used for therapist alerts, and confirm the error-alert channel is set correctly. 5. Verify your Google Sheets columns match the workflow’s expected fields (for example session_id, checkin_sent, checkin_message_sent, therapist_slack_id) before activating.

View

Detect and route customer escalations with Claude, Slack and Linear

## Quick Overview This workflow receives support messages via a webhook, normalizes payloads from Gmail, Zendesk, Intercom, and HelpScout, and uses Anthropic Claude to detect escalation signals and severity, then posts alerts to Slack and creates Linear tickets for actionable cases. ## How it works 1. Receives an inbound support message via a POST webhook. 2. Normalizes the incoming payload (Gmail, Zendesk, Intercom, HelpScout, or a raw test payload) into a consistent schema with customer details, subject, body text, and a source URL. 3. Sends the normalized message to Anthropic Claude and parses the response into structured JSON containing escalation flags, severity, trigger phrases, a summary, and a suggested reply opening. 4. Stops processing silently when the message is not an escalation (severity is none). 5. Builds a formatted Slack alert and Linear issue payload, including SLA guidance, detected signals, and links back to the original conversation. 6. Posts the escalation alert to a configured Slack channel. 7. Creates a Linear ticket for critical, high, and medium severity escalations and sends a Slack DM to a manager for critical and high cases. ## Setup 1. Add an Anthropic API credential for the Anthropic Chat Model node. 2. Add a Slack OAuth2 credential, set the target channel (for example, #escalations), and set the manager’s Slack user ID for direct messages. 3. Add a Linear OAuth2 credential and replace the placeholder Linear team ID used when creating tickets. 4. Copy the webhook URL from the webhook trigger and configure Gmail/Zendesk/Intercom/HelpScout (or your custom source) to POST message payloads to it in one of the supported formats.

View

Triage construction incidents with GPT-4o, Slack, Gmail and Google Sheets

## Quick Overview This workflow ingests construction incident webhooks, normalizes the payload, and uses OpenAI GPT-4o-mini to classify each incident by type and urgency, then routes alerts to Slack and Gmail and logs incidents to Google Sheets, with a daily Slack digest generated from the sheet. ## How it works 1. Receives an incoming incident via a POST webhook. 2. Normalizes the incoming Procore/Fieldwire-style payload into a consistent incident object (ID, title, description, location, reporter, assignee, and timestamps). 3. Sends the incident details to OpenAI (GPT-4o-mini) to classify issue type and urgency and generate a short summary, recommended action, and tags. 4. Routes incidents by urgency, sending Critical incidents to Slack with an @channel mention and emailing details to a project manager via Gmail. 5. Sends High-urgency incidents to Slack as a formatted notice. 6. Appends every incident to a Google Sheets log with status set to open. 7. Runs daily at 18:00 server time, reads the incident log from Google Sheets, builds an urgency-grouped digest, and posts it to a Slack channel. ## Setup 1. Add credentials for OpenAI, Slack (OAuth2), Gmail (OAuth2), and Google Sheets (OAuth2). 2. Copy the webhook URL from the Webhook trigger and register it in your source system (for example, Procore or Fieldwire) as the incident-created endpoint. 3. Replace the placeholder Slack channel IDs for Critical, High, Digest, and Error alerts. 4. Update the Gmail recipient address ([email protected]) to your real project manager email. 5. Set the Google Sheets spreadsheet (document ID) and ensure the target sheet exists with columns that match the incident log fields used by the workflow. 6. Confirm the schedule trigger time (cron: 0 18 * * *) matches your desired timezone/server time for the daily digest.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

Zendesk ticket summarizer with Pinecone, OpenAI, and Slack

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Zendesk Ticket Summarizer with Pinecone, OpenAI, and Slack

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - OpenAI Chat Model1

Block 2 - Pinecone Vector Store2

Block 3 - Embeddings OpenAI2

Block 4 - Send to Slack channel

Block 5 - Default Data Loader1

Block 6 - Wait1

Block 7 - Daily trigger

Block 8 - Get tickets

Block 9 - Pinecone Vector Store - Tickets

Block 10 - Embeddings OpenAI

Block 11 - AI Agent - Summary generator

Block 12 - Sticky Note

Block 13 - Sticky Note1

Block 14 - Sticky Note2

Block 15 - Sticky Note3

Block 16 - Sticky Note4

Block 17 - Sticky Note5

Block 18 - Sticky Note6

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions