Block 1 - Zendesk
- Type / Role
- n8n-nodes-base.zendesk - zendesk
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
Analyze and Explore your ZenDesk Support Requests using AI Powered Knowledge Graph This template helps you create an interactive InfraNodus knowledge graph for your ZenDes...
n8n-nodes-base.zendesk, n8n-nodes-base.httprequest, n8n-nodes-base.code, n8n-nodes-base.wait, n8n-nodes-base.telegram, n8n-nodes-base.gmail, n8n-nodes-base.scheduletrigger, n8n-nodes-base.slack
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by InfraNodus.
Original n8n.io sourceThis template helps you create an interactive InfraNodus knowledge graph for your ZenDesk tickets using any search criteria (e.g. after a certain date, specific status, sender, keyword) that will automatically be sent to a selected Slack channel.
Here's an example of the InfraNodus graph that shows the main topics and gaps in ZenDesk support tickets:
You can start this workflow
Once started, it will perform a ZenDesk tickets search with the default or your custom criteria. Then it will use the search results to generate an InfraNodus graph (or add the new data to an existing one), and — finally — use the InfraNodus AI endpoints to generate a topical summary and a product business idea based on the blind spots identified. The results are delivered a channel of your choice.
Here's a description step by step:
You need an InfraNodus API account and key to use this workflow. You also need a ZenDesk account. It takes about 5 minutes to set everything up.
1. What are the best use cases to try?
I love to set the graph to deliver me a daily visual briefing of what's happening in my support portal. It shows me the main topics and gaps and generates product ideas based on them. Great to keep the pulse on the business.
I also really like generating a graph for the past week manually, using the form, and then exploring the graph in InfraNodus directly using the customer feedback analysis workflow to:
2. Why use the graph and not just AI summary?
AI summary will just give you generic results. You'll see what you already know. Using the graph helps you deconstruct the discourse and get a much more nuanced understanding of the main pain points and interests of your customers. The auto-generated InfraNodus summary and business ideas have a direct explainable connection to the discourse, so you can always see where they are coming from and maintain the focus on all the topics, rather than the most prominent ones.
Additionally, having an interactive graph opens a possibility to explore your customers' concerns in a more engaging way, finding the topics and concepts that are relevant to your interests or to your agents' expertise, helping you find the conversations that you'd otherwise have missed.
3. Is my customers' data safe?
Absolutely. InfraNodus' terms of use and privacy policy state that the customers' data and text graphs are not used in AI training and are not offered to any third parties. Its underlying API system uses the Open API which explicitly states that data is not used for training either. So all the customers' data are private and safe. As an extra precaution, you can always delete the graphs after you analyzed them, in which case there is no trace of this data left on the servers.
Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20447530961308-Zendesk-Tickets-Summarization-Sentiment-Analysis-and-Slack-Integration-with-n8n-and-InfraNodus
For support with this template, please, contact https://support.noduslabs.com
For more InfraNodus n8n workflows, please, see our creators page: https://n8n.io/creators/infranodus/
To learn more about InfraNodus, GraphRAG, and knowledge graph analysis: https://infranodus.com
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.
| Workflow | Zendesk: visual summarization, sentiment analysis, and Slack integration |
|---|---|
| Complexity | advanced |
| Nodes | 23 |
| Categories | Ticket Management, AI Summarization |
| Author | InfraNodus |
| Published | 05 Jun 2025 |
Use the JSON export at /data/workflows/4688/4688.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
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.
Analyze and Explore your ZenDesk Support Requests using AI Powered Knowledge Graph This template helps you create an interactive InfraNodus knowledge graph for your ZenDes...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
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 Summarization use case.